DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Office Action is in response to the application filed 11/03/2025. Claims 1-43 are presently pending and are presented for examination.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 15, and 30 are rejected under 35 U.S.C. § 102(a)(1) as being unpatentable over Flood et al., US-20190102623-A1, hereinafter referred to as Flood.
As per claim 1
Flood discloses [a] method performed by data processing apparatus, the method comprising (one or more mobile machine(s) 108 operating to perform one or more forestry operations – Flood ¶32):
deploying at least one drone that includes a remote sensing device (FIG. 1 illustratively shows that UAV 104 includes an image capture component 122. UAV 104 travels along a flight path within worksite 102, instructions to control mobile machine 108 to perform a ground disturbance correction – Flood ¶32 & ¶106);
collecting, by the remote sensing device of the at least one drone, a scan of a geographic area (FIG. 1 illustratively shows that UAV 104 includes an image capture component 122. UAV 104 travels along a flight path within worksite 102…UAV 104 is also configured to communicate with mobile machines 108 to obtain sensor information sensed by sensors positioned on each of the machines, image capture component 122 can identify worksite area 106…particular areas of interest, trees, tree properties – Flood ¶32 & ¶48);
determining, based on the scan of the geographic area, a modification to the geographic area required to achieve a target state of the geographic area (block 406, ground disturbance identification logic 260 obtains captured images of worksite area 106. For example, ground disturbance identification logic 260 can obtain images captured by image capture component 122 of UAV system 104, At block 416, area of correction identification component 336 identifies a particular sub-area of the worksite area 106 that requires repair and generates an action signal…ground disturbance image processing logic 332 can identify points on the mapped representation of worksite area 106 – Flood ¶99 & ¶104);
determining, based on the collected scan, a given device that will be deployed to make the modification required to achieve the target state of the geographic area (block 406, ground disturbance identification logic 260 obtains captured images of worksite area 106. For example, ground disturbance identification logic 260 can obtain images captured by image capture component 122 of UAV system 104, At block 418, corrective action selection component 338 selects a particular corrective action…particular action selected by corrective action selection component 338 can include any of a mobile machine action, as indicated at block 452, a planned path update action, as indicated at block 454, a traction-assist action, as indicated at block 456, a UAV action, as indicated at block 458, among other actions as shown at block 460, mobile machine action, as indicated at block 452, can include instructions to control mobile machine 108 to perform a ground disturbance correction…instructions to modify a prescribed travel route of machine 108 – Flood ¶99 & ¶105 & ¶106);
deploying the given device in the geographic area with instructions to make the modification required to achieve the target state of the geographic area, wherein deploying the device comprises causing the given device to navigate within the geographic area (At block 418, corrective action selection component 338 selects a particular corrective action…particular action selected by corrective action selection component 338 can include any of a mobile machine action, as indicated at block 452, a planned path update action, as indicated at block 454, a traction-assist action, as indicated at block 456, a UAV action, as indicated at block 458, among other actions as shown at block 460, mobile machine action, as indicated at block 452, can include instructions to control mobile machine 108 to perform a ground disturbance correction…instructions to modify a prescribed travel route of machine 108 – Flood ¶105 & ¶106).
As per claim 15
Flood discloses [a] system comprising (one or more mobile machine(s) 108 operating to perform one or more forestry operations – Flood ¶32):
one or more memory devices (removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data – Flood ¶191);
at least one computing device configured to interact with the one or more memory devices and execute instructions that cause the at least one computing device to perform operations comprising (removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data – Flood ¶191):
deploying at least one drone that includes a remote sensing device (FIG. 1 illustratively shows that UAV 104 includes an image capture component 122. UAV 104 travels along a flight path within worksite 102, instructions to control mobile machine 108 to perform a ground disturbance correction – Flood ¶32 & ¶106);
collecting, by the remote sensing device of the at least one drone, a scan of a geographic area (FIG. 1 illustratively shows that UAV 104 includes an image capture component 122. UAV 104 travels along a flight path within worksite 102…UAV 104 is also configured to communicate with mobile machines 108 to obtain sensor information sensed by sensors positioned on each of the machines, image capture component 122 can identify worksite area 106…particular areas of interest, trees, tree properties – Flood ¶32 & ¶48);
determining, based on the scan of the geographic area, a modification to the geographic area required to achieve a target state of the geographic area (block 406, ground disturbance identification logic 260 obtains captured images of worksite area 106. For example, ground disturbance identification logic 260 can obtain images captured by image capture component 122 of UAV system 104, At block 416, area of correction identification component 336 identifies a particular sub-area of the worksite area 106 that requires repair and generates an action signal…ground disturbance image processing logic 332 can identify points on the mapped representation of worksite area 106 – Flood ¶99 & ¶104);
determining, based on the collected scan, a given device that will be deployed to make the modification required to achieve the target state of the geographic area (block 406, ground disturbance identification logic 260 obtains captured images of worksite area 106. For example, ground disturbance identification logic 260 can obtain images captured by image capture component 122 of UAV system 104, At block 418, corrective action selection component 338 selects a particular corrective action…particular action selected by corrective action selection component 338 can include any of a mobile machine action, as indicated at block 452, a planned path update action, as indicated at block 454, a traction-assist action, as indicated at block 456, a UAV action, as indicated at block 458, among other actions as shown at block 460, mobile machine action, as indicated at block 452, can include instructions to control mobile machine 108 to perform a ground disturbance correction…instructions to modify a prescribed travel route of machine 108 – Flood ¶99 & ¶105 & ¶106);
deploying the given device in the geographic area with instructions to make the modification required to achieve the target state of the geographic area, wherein deploying the device comprises causing the given device to navigate within the geographic area (At block 418, corrective action selection component 338 selects a particular corrective action…particular action selected by corrective action selection component 338 can include any of a mobile machine action, as indicated at block 452, a planned path update action, as indicated at block 454, a traction-assist action, as indicated at block 456, a UAV action, as indicated at block 458, among other actions as shown at block 460, mobile machine action, as indicated at block 452, can include instructions to control mobile machine 108 to perform a ground disturbance correction…instructions to modify a prescribed travel route of machine 108 – Flood ¶105 & ¶106).
As per claim 30
Flood discloses [a] non-transitory computer readable medium storing instructions that, upon execution by at least one computing device, cause the at least one computing device to perform operations comprising (removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data – Flood ¶191):
deploying at least one drone that includes a remote sensing device (FIG. 1 illustratively shows that UAV 104 includes an image capture component 122. UAV 104 travels along a flight path within worksite 102, instructions to control mobile machine 108 to perform a ground disturbance correction – Flood ¶32 & ¶106);
collecting, by the remote sensing device of the at least one drone, a scan of a geographic area (FIG. 1 illustratively shows that UAV 104 includes an image capture component 122. UAV 104 travels along a flight path within worksite 102…UAV 104 is also configured to communicate with mobile machines 108 to obtain sensor information sensed by sensors positioned on each of the machines, image capture component 122 can identify worksite area 106…particular areas of interest, trees, tree properties – Flood ¶32 & ¶48);
determining, based on the scan of the geographic area, a modification to the geographic area required to achieve a target state of the geographic area (block 406, ground disturbance identification logic 260 obtains captured images of worksite area 106. For example, ground disturbance identification logic 260 can obtain images captured by image capture component 122 of UAV system 104, At block 416, area of correction identification component 336 identifies a particular sub-area of the worksite area 106 that requires repair and generates an action signal…ground disturbance image processing logic 332 can identify points on the mapped representation of worksite area 106 – Flood ¶99 & ¶104);
determining, based on the collected scan, a given device that will be deployed to make the modification required to achieve the target state of the geographic area (block 406, ground disturbance identification logic 260 obtains captured images of worksite area 106. For example, ground disturbance identification logic 260 can obtain images captured by image capture component 122 of UAV system 104, At block 418, corrective action selection component 338 selects a particular corrective action…particular action selected by corrective action selection component 338 can include any of a mobile machine action, as indicated at block 452, a planned path update action, as indicated at block 454, a traction-assist action, as indicated at block 456, a UAV action, as indicated at block 458, among other actions as shown at block 460, mobile machine action, as indicated at block 452, can include instructions to control mobile machine 108 to perform a ground disturbance correction…instructions to modify a prescribed travel route of machine 108 – Flood ¶99 & ¶105 & ¶106);
deploying the given device in the geographic area with instructions to make the modification required to achieve the target state of the geographic area, wherein deploying the device comprises causing the given device to navigate within the geographic area (At block 418, corrective action selection component 338 selects a particular corrective action…particular action selected by corrective action selection component 338 can include any of a mobile machine action, as indicated at block 452, a planned path update action, as indicated at block 454, a traction-assist action, as indicated at block 456, a UAV action, as indicated at block 458, among other actions as shown at block 460, mobile machine action, as indicated at block 452, can include instructions to control mobile machine 108 to perform a ground disturbance correction…instructions to modify a prescribed travel route of machine 108 – Flood ¶105 & ¶106).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 2, 17, and 31 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, as per claims 1, 15, and 30, respectfully, and further in view of Degnan et al., US-20230042867-A1, hereinafter referred to as Degnan.
As per claim 2
Flood further discloses wherein: the remote sensing device comprises a Light Detection and Ranging (LIDAR) device (digital representations of worksite area 106. LIDAR/radar imaging component 244 scans worksite area 106 – Flood ¶49).
Flood does not specifically disclose collecting a scan of the geographic area comprises generating a LIDAR mapping of a candidate solar field or wind power field.
However, Degnan teaches collecting a scan of the geographic area comprises generating a LIDAR mapping of a candidate solar field or wind power field (the data from the lidar camera may be used for perception, localization, and navigation, create an optimum cut pattern, steer the vehicle along the predetermined route at the correct speed, and to control the cut parameters to achieve the desired pattern (e.g., grass cut height, inspection of object (e.g., inspection of solar panels - Degnan ¶8 & ¶11 & ¶189).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Degnan teaches autonomous electric lawn mowers.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with autonomous electric lawn mowers, as taught by Degnan, with a reasonable expectation of success so that the mowing system is operable to safely stop if the obstructions or sensor occlusions are deemed to not allow the mower to continue safe operations, and to improve the health of the grass, see Degnan ¶18 & ¶74 for details.
As per claim 17
Flood further discloses wherein: the remote sensing device comprises a Light Detection and Ranging (LIDAR) device (digital representations of worksite area 106. LIDAR/radar imaging component 244 scans worksite area 106 – Flood ¶49).
Flood does not specifically disclose collecting a scan of the geographic area comprises generating a LIDAR mapping of a candidate solar field or wind power field.
However, Degnan teaches collecting a scan of the geographic area comprises generating a LIDAR mapping of a candidate solar field or wind power field (the data from the lidar camera may be used for perception, localization, and navigation, create an optimum cut pattern, steer the vehicle along the predetermined route at the correct speed, and to control the cut parameters to achieve the desired pattern (e.g., grass cut height, inspection of object (e.g., inspection of solar panels - Degnan ¶8 & ¶11 & ¶189).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Degnan teaches autonomous electric lawn mowers.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with autonomous electric lawn mowers, as taught by Degnan, with a reasonable expectation of success so that the mowing system is operable to safely stop if the obstructions or sensor occlusions are deemed to not allow the mower to continue safe operations, and to improve the health of the grass, see Degnan ¶18 & ¶74 for details.
As per claim 31
Flood further discloses wherein: the remote sensing device comprises a Light Detection and Ranging (LIDAR) device (digital representations of worksite area 106. LIDAR/radar imaging component 244 scans worksite area 106 – Flood ¶49).
Flood does not specifically disclose collecting a scan of the geographic area comprises generating a LIDAR mapping of a candidate solar field or wind power field.
However, Degnan teaches collecting a scan of the geographic area comprises generating a LIDAR mapping of a candidate solar field or wind power field (the data from the lidar camera may be used for perception, localization, and navigation, create an optimum cut pattern, steer the vehicle along the predetermined route at the correct speed, and to control the cut parameters to achieve the desired pattern (e.g., grass cut height, inspection of object (e.g., inspection of solar panels - Degnan ¶8 & ¶11 & ¶189).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Degnan teaches autonomous electric lawn mowers.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with autonomous electric lawn mowers, as taught by Degnan, with a reasonable expectation of success so that the mowing system is operable to safely stop if the obstructions or sensor occlusions are deemed to not allow the mower to continue safe operations, and to improve the health of the grass, see Degnan ¶18 & ¶74 for details.
Claims 3, 18, and 32 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, as per claims 1, 15, and 30, respectfully, and further in view of Jamison, US-20170055433-A1, hereinafter referred to as Jamison.
As per claim 3
Flood does not specifically disclose wherein: determining a modification to the geographic area required to achieve a target state of the geographic area comprises determining that vegetation in the geographic area is required to be cut to achieve a height of the vegetation that is below a specified height; and deploying the given device in the geographic area comprises causing a self-driving device to perform operations comprising: navigating within the geographic area; and cutting the vegetation to a height that is less than the specified height.
However, Jamison teaches wherein: determining a modification to the geographic area required to achieve a target state of the geographic area comprises determining that vegetation in the geographic area is required to be cut to achieve a height of the vegetation that is below a specified height; and deploying the given device in the geographic area comprises causing a self-driving device to perform operations comprising: navigating within the geographic area; and cutting the vegetation to a height that is less than the specified height (comprises the acts of receiving a representation of an image defined by a first set of points (e.g., cutting plants at the first set of points to a first height) and a second set of points (e.g., cutting plants at the second set of points to a second height), and traversing the surface with a sculpting mechanism operatively associated with a navigation system configured to detect a position of the sculpting mechanism relative to each point in the first set of points and the second set of points… responsive to a location determined by the navigation system, an act of selectively actuating the sculpting mechanism at least the first set of points to perform a first sculpting action to yield, either contemporaneously with the act of selectively actuating the sculpting mechanism or at a later time, different physical characteristics along the surface as between the first set of points and the second set of points…sculpting mechanism is, in at least one other aspect, a mower, a combine, a sod harvester and the act of selective actuation at the first set of points includes actuating the mower at a first height, and the selective actuation at the second set of points includes actuating the mower at a second height, a first set of points on the property and traversing the real property with a mechanism operatively associated with both a control system and a navigation system configured to detect both a location of the mechanism and a spatial position (e.g., height, etc.) of at least a portion of the mechanism relative to the first set of points - Jamison ¶8 & ¶10).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Jamison teaches methods to form an aerially-viewable approximation of a target image of an agricultural field.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with methods to form an aerially-viewable approximation of a target image of an agricultural field, as taught by Jamison, with a reasonable expectation of success to advantageously reduce the cost of creating such graphics, relative to such conventional methods, such as the cost of wasted seed (e.g., seed that is planted and later destroyed to create the graphic), the cost of fuel for additional passes through a field (e.g., to mow down or flatten the unwanted areas of the graphic) and, of course, the time differential cost, see Jamison ¶67 for details.
As per claim 18
Flood does not specifically disclose wherein: determining a modification to the geographic area required to achieve a target state of the geographic area comprises determining that vegetation in the geographic area is required to be cut to achieve a height of the vegetation that is below a specified height; and deploying the given device in the geographic area comprises causing a self-driving device to perform operations comprising: navigating within the geographic area; and cutting the vegetation to a height that is less than the specified height.
However, Jamison teaches wherein: determining a modification to the geographic area required to achieve a target state of the geographic area comprises determining that vegetation in the geographic area is required to be cut to achieve a height of the vegetation that is below a specified height; and deploying the given device in the geographic area comprises causing a self-driving device to perform operations comprising: navigating within the geographic area; and cutting the vegetation to a height that is less than the specified height (comprises the acts of receiving a representation of an image defined by a first set of points (e.g., cutting plants at the first set of points to a first height) and a second set of points (e.g., cutting plants at the second set of points to a second height), and traversing the surface with a sculpting mechanism operatively associated with a navigation system configured to detect a position of the sculpting mechanism relative to each point in the first set of points and the second set of points… responsive to a location determined by the navigation system, an act of selectively actuating the sculpting mechanism at least the first set of points to perform a first sculpting action to yield, either contemporaneously with the act of selectively actuating the sculpting mechanism or at a later time, different physical characteristics along the surface as between the first set of points and the second set of points…sculpting mechanism is, in at least one other aspect, a mower, a combine, a sod harvester and the act of selective actuation at the first set of points includes actuating the mower at a first height, and the selective actuation at the second set of points includes actuating the mower at a second height, a first set of points on the property and traversing the real property with a mechanism operatively associated with both a control system and a navigation system configured to detect both a location of the mechanism and a spatial position (e.g., height, etc.) of at least a portion of the mechanism relative to the first set of points - Jamison ¶8 & ¶10).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Jamison teaches methods to form an aerially-viewable approximation of a target image of an agricultural field.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with methods to form an aerially-viewable approximation of a target image of an agricultural field, as taught by Jamison, with a reasonable expectation of success to advantageously reduce the cost of creating such graphics, relative to such conventional methods, such as the cost of wasted seed (e.g., seed that is planted and later destroyed to create the graphic), the cost of fuel for additional passes through a field (e.g., to mow down or flatten the unwanted areas of the graphic) and, of course, the time differential cost, see Jamison ¶67 for details.
As per claim 32
Flood does not specifically disclose wherein: determining a modification to the geographic area required to achieve a target state of the geographic area comprises determining that vegetation in the geographic area is required to be cut to achieve a height of the vegetation that is below a specified height; and deploying the given device in the geographic area comprises causing a self-driving device to perform operations comprising: navigating within the geographic area; and cutting the vegetation to a height that is less than the specified height.
However, Jamison teaches wherein: determining a modification to the geographic area required to achieve a target state of the geographic area comprises determining that vegetation in the geographic area is required to be cut to achieve a height of the vegetation that is below a specified height; and deploying the given device in the geographic area comprises causing a self-driving device to perform operations comprising: navigating within the geographic area; and cutting the vegetation to a height that is less than the specified height (comprises the acts of receiving a representation of an image defined by a first set of points (e.g., cutting plants at the first set of points to a first height) and a second set of points (e.g., cutting plants at the second set of points to a second height), and traversing the surface with a sculpting mechanism operatively associated with a navigation system configured to detect a position of the sculpting mechanism relative to each point in the first set of points and the second set of points… responsive to a location determined by the navigation system, an act of selectively actuating the sculpting mechanism at least the first set of points to perform a first sculpting action to yield, either contemporaneously with the act of selectively actuating the sculpting mechanism or at a later time, different physical characteristics along the surface as between the first set of points and the second set of points…sculpting mechanism is, in at least one other aspect, a mower, a combine, a sod harvester and the act of selective actuation at the first set of points includes actuating the mower at a first height, and the selective actuation at the second set of points includes actuating the mower at a second height, a first set of points on the property and traversing the real property with a mechanism operatively associated with both a control system and a navigation system configured to detect both a location of the mechanism and a spatial position (e.g., height, etc.) of at least a portion of the mechanism relative to the first set of points - Jamison ¶8 & ¶10).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Jamison teaches methods to form an aerially-viewable approximation of a target image of an agricultural field.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with methods to form an aerially-viewable approximation of a target image of an agricultural field, as taught by Jamison, with a reasonable expectation of success to advantageously reduce the cost of creating such graphics, relative to such conventional methods, such as the cost of wasted seed (e.g., seed that is planted and later destroyed to create the graphic), the cost of fuel for additional passes through a field (e.g., to mow down or flatten the unwanted areas of the graphic) and, of course, the time differential cost, see Jamison ¶67 for details.
Claims 4, 19, and 33 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, and Jamison, as per claims 3, 18, and 32, respectfully, and further in view of Vild et al., US-20220132748-A1, and Fox et al., US-11074447-B1, hereinafter referred to as Vild, and Fox.
As per claim 4
Flood does not specifically disclose further comprising: training a machine learning model to predict vegetation growth using a set of historical data, including at least one of vegetation growth history for the geographic area, vegetation management activity, or weather data.
However, Vild teaches further comprising: training a machine learning model to predict vegetation growth using a set of historical data, including at least one of vegetation growth history for the geographic area, vegetation management activity, or weather data (wherein selecting, by the processor, one or more machine learning models is further based on one or more prediction features identified from the obtained data, the one or more prediction features including at least one of a growing region of the plant, environmental conditions…stage of growth of the plant, wherein the known plant information includes at least one of historic growing information about the one or more other plants, information can also be specific about a growing region of the collected plant and/or plant product - Vild ¶31 & ¶32 & ¶88).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Vild teaches systems and methods for identifying pre-harvest latent infection in plants.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with systems and methods for identifying pre-harvest latent infection in plants, as taught by Vild, with a reasonable expectation of success for reducing plant product waste, improving customer acceptance, and provide a higher quality of plant products, see Vild ¶34 for details.
Flood does not specifically disclose generating a proposed vegetation management plan based on a predicted vegetation growth output by the machine learning model, wherein the proposed vegetation management plan specifies different vegetation cutting schedules for different subsections of the geographic area based on differences in predicted vegetation growth in the different subsections, wherein: deploying the given device in the geographic area comprises deploying the given device to the different subsections of the geographic area according to the proposed vegetation management plan.
However, Fox teaches generating a proposed vegetation management plan based on a predicted vegetation growth output by the machine learning model, wherein the proposed vegetation management plan specifies different vegetation cutting schedules for different subsections of the geographic area based on differences in predicted vegetation growth in the different subsections, wherein: deploying the given device in the geographic area comprises deploying the given device to the different subsections of the geographic area according to the proposed vegetation management plan (aerial vehicle 130 may be an unmanned aerial vehicle. For example, the aerial vehicle 130 may be four or six rotor drone…aerial vehicle 130 may include one or more cameras 132…aerial vehicle 130 may further include a flight path controller 138. The flight path controller 138 may communicate with the land analysis system 120 to receive flight path parameters…the land analysis system 120 itself could identify areas of interest based on the augmented reality view, and set and/or adjust flight parameters accordingly to modify the flight path of the aerial vehicle 130 in real-time, if one or more of the height…is less than one or more of the threshold height…AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130…transmit…a message…to perform the opposite operation…The AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 may also generate a notification for transmission to a user device 102 via the network 110 (e.g., a push notification) indicating that the plant (or group of plants) do not need to be pruned, the plant (or group of plants) should be pruned later than scheduled, and/or additional plants should be planted in the corresponding geographic area…the AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130 at the direction of a component of the land analysis system 120 can generate and transmit a message to cause the irrigation system 150 to water the plant (or group of plants) automatically, more frequently, and/or less frequently. - Fox Column 12 Line 27 – Column 13 Line 51 & Column 27 Line 35 – Column 27 Line 65).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Fox teaches a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site, as taught by Fox, with a reasonable expectation of success to estimate plant health, see Fox ¶44 for details.
As per claim 19
Flood does not specifically disclose wherein the operations comprise: training a machine learning model to predict vegetation growth using a set of historical data, including at least one of vegetation growth history for the geographic area, vegetation management activity, or weather data.
However, Vild teaches wherein the operations comprise: training a machine learning model to predict vegetation growth using a set of historical data, including at least one of vegetation growth history for the geographic area, vegetation management activity, or weather data (wherein selecting, by the processor, one or more machine learning models is further based on one or more prediction features identified from the obtained data, the one or more prediction features including at least one of a growing region of the plant, environmental conditions…stage of growth of the plant, wherein the known plant information includes at least one of historic growing information about the one or more other plants, information can also be specific about a growing region of the collected plant and/or plant product - Vild ¶31 & ¶32 & ¶88).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Vild teaches systems and methods for identifying pre-harvest latent infection in plants.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with systems and methods for identifying pre-harvest latent infection in plants, as taught by Vild, with a reasonable expectation of success for reducing plant product waste, improving customer acceptance, and provide a higher quality of plant products, see Vild ¶34 for details.
Flood does not specifically disclose generating a proposed vegetation management plan based on a predicted vegetation growth output by the machine learning model, wherein the proposed vegetation management plan specifies different vegetation cutting schedules for different subsections of the geographic area based on differences in predicted vegetation growth in the different subsections, wherein: deploying the given device in the geographic area comprises deploying the given device to the different subsections of the geographic area according to the proposed vegetation management plan.
However, Fox teaches generating a proposed vegetation management plan based on a predicted vegetation growth output by the machine learning model, wherein the proposed vegetation management plan specifies different vegetation cutting schedules for different subsections of the geographic area based on differences in predicted vegetation growth in the different subsections, wherein: deploying the given device in the geographic area comprises deploying the given device to the different subsections of the geographic area according to the proposed vegetation management plan (aerial vehicle 130 may be an unmanned aerial vehicle. For example, the aerial vehicle 130 may be four or six rotor drone…aerial vehicle 130 may include one or more cameras 132…aerial vehicle 130 may further include a flight path controller 138. The flight path controller 138 may communicate with the land analysis system 120 to receive flight path parameters…the land analysis system 120 itself could identify areas of interest based on the augmented reality view, and set and/or adjust flight parameters accordingly to modify the flight path of the aerial vehicle 130 in real-time, if one or more of the height…is less than one or more of the threshold height…AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130…transmit…a message…to perform the opposite operation…The AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 may also generate a notification for transmission to a user device 102 via the network 110 (e.g., a push notification) indicating that the plant (or group of plants) do not need to be pruned, the plant (or group of plants) should be pruned later than scheduled, and/or additional plants should be planted in the corresponding geographic area…the AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130 at the direction of a component of the land analysis system 120 can generate and transmit a message to cause the irrigation system 150 to water the plant (or group of plants) automatically, more frequently, and/or less frequently. - Fox Column 12 Line 27 – Column 13 Line 51 & Column 27 Line 35 – Column 27 Line 65).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Fox teaches a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site, as taught by Fox, with a reasonable expectation of success to estimate plant health, see Fox ¶44 for details.
As per claim 33
Flood does not specifically disclose wherein the operations comprise: training a machine learning model to predict vegetation growth using a set of historical data, including at least one of vegetation growth history for the geographic area, vegetation management activity, or weather data.
However, Vild teaches wherein the operations comprise: training a machine learning model to predict vegetation growth using a set of historical data, including at least one of vegetation growth history for the geographic area, vegetation management activity, or weather data (wherein selecting, by the processor, one or more machine learning models is further based on one or more prediction features identified from the obtained data, the one or more prediction features including at least one of a growing region of the plant, environmental conditions…stage of growth of the plant, wherein the known plant information includes at least one of historic growing information about the one or more other plants, information can also be specific about a growing region of the collected plant and/or plant product - Vild ¶31 & ¶32 & ¶88).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Vild teaches systems and methods for identifying pre-harvest latent infection in plants.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with systems and methods for identifying pre-harvest latent infection in plants, as taught by Vild, with a reasonable expectation of success for reducing plant product waste, improving customer acceptance, and provide a higher quality of plant products, see Vild ¶34 for details.
Flood does not specifically disclose generating a proposed vegetation management plan based on a predicted vegetation growth output by the machine learning model, wherein the proposed vegetation management plan specifies different vegetation cutting schedules for different subsections of the geographic area based on differences in predicted vegetation growth in the different subsections, wherein: deploying the given device in the geographic area comprises deploying the given device to the different subsections of the geographic area according to the proposed vegetation management plan.
However, Fox teaches generating a proposed vegetation management plan based on a predicted vegetation growth output by the machine learning model, wherein the proposed vegetation management plan specifies different vegetation cutting schedules for different subsections of the geographic area based on differences in predicted vegetation growth in the different subsections, wherein: deploying the given device in the geographic area comprises deploying the given device to the different subsections of the geographic area according to the proposed vegetation management plan (aerial vehicle 130 may be an unmanned aerial vehicle. For example, the aerial vehicle 130 may be four or six rotor drone…aerial vehicle 130 may include one or more cameras 132…aerial vehicle 130 may further include a flight path controller 138. The flight path controller 138 may communicate with the land analysis system 120 to receive flight path parameters…the land analysis system 120 itself could identify areas of interest based on the augmented reality view, and set and/or adjust flight parameters accordingly to modify the flight path of the aerial vehicle 130 in real-time, if one or more of the height…is less than one or more of the threshold height…AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130…transmit…a message…to perform the opposite operation…The AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 may also generate a notification for transmission to a user device 102 via the network 110 (e.g., a push notification) indicating that the plant (or group of plants) do not need to be pruned, the plant (or group of plants) should be pruned later than scheduled, and/or additional plants should be planted in the corresponding geographic area…the AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130 at the direction of a component of the land analysis system 120 can generate and transmit a message to cause the irrigation system 150 to water the plant (or group of plants) automatically, more frequently, and/or less frequently. - Fox Column 12 Line 27 – Column 13 Line 51 & Column 27 Line 35 – Column 27 Line 65).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Fox teaches a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site, as taught by Fox, with a reasonable expectation of success to estimate plant health, see Fox ¶44 for details.
Claims 5, 9, 20, 24, 34, and 38 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, and Jamison, as per claims 3, 18, and 32, respectfully, and further in view of Ono, US-20080097699-A1, hereinafter referred to as Ono.
As per claim 5
Flood does not specifically disclose further comprising: obtaining, from data collected using one or more sensors, a terrain report specifying one or more obstacles that will interfere with the navigation of the self-driving device within the geographic area; generating, based on the terrain report, a navigation path that reduces the interference of the one or more obstacles with the navigation of the self-driving device within the geographic area; and causing the self-driving device to navigate within the geographic area according to the navigation path.
However, Ono teaches further comprising: obtaining, from data collected using one or more sensors, a terrain report specifying one or more obstacles that will interfere with the navigation of the self-driving device within the geographic area; generating, based on the terrain report, a navigation path that reduces the interference of the one or more obstacles with the navigation of the self-driving device within the geographic area; and causing the self-driving device to navigate within the geographic area according to the navigation path (group of sensors of the vehicle motion control device for detecting the external environment state, there are provided a camera 18, At next step 110, a risk at passage time TTC when the driver's vehicle passes through the shortest avoidance trajectory is created as a TTC risk map (passage time risk map), based on the passage time TTC on the shortest avoidance trajectory obtained at step 108 and the future risk map created at step 106 - Ono ¶67 & ¶122).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Ono teaches a vehicle motion control device capable of realizing optimum avoidance control in the case of an emergency.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a vehicle motion control device capable of realizing optimum avoidance control in the case of an emergency, as taught by Ono, with a reasonable expectation of success to improve the predication precision of the risk by correcting action predicated based on information of the road environment, weather and time zone, see Ono ¶109 for details.
As per claim 9
Flood further discloses further comprising: detecting, by the self-driving device while navigating within the geographic area, an actionable condition; reporting, by the self-driving device, the actionable condition to a system controller configured to interact with the self-driving device and one or more other devices; and causing, by the system controller, the one or more other devices to perform operations that resolve the actionable condition (UAV 104 is also configured to communicate with mobile machines 108 to obtain sensor information sensed by sensors positioned on each of the machines, mobile machine action, as indicated at block 452, can include instructions to control mobile machine 108 to perform a ground disturbance correction…instructions to modify a prescribed travel route of machine 108, block 420 , ground disturbance correction logic 334 generates and outputs an indication of the corrective action selected to repair the particular sub-area – Flood ¶32 & ¶106 & ¶107).
As per claim 20
Flood does not specifically disclose wherein the operations comprise: obtaining, from data collected using one or more sensors, a terrain report specifying one or more obstacles that will interfere with the navigation of the self-driving device within the geographic area; generating, based on the terrain report, a navigation path that reduces the interference of the one or more obstacles with the navigation of the self-driving device within the geographic area; and causing the self-driving device to navigate within the geographic area according to the navigation path.
However, Ono teaches further comprising: obtaining, from data collected using one or more sensors, a terrain report specifying one or more obstacles that will interfere with the navigation of the self-driving device within the geographic area; generating, based on the terrain report, a navigation path that reduces the interference of the one or more obstacles with the navigation of the self-driving device within the geographic area; and causing the self-driving device to navigate within the geographic area according to the navigation path (group of sensors of the vehicle motion control device for detecting the external environment state, there are provided a camera 18, At next step 110, a risk at passage time TTC when the driver's vehicle passes through the shortest avoidance trajectory is created as a TTC risk map (passage time risk map), based on the passage time TTC on the shortest avoidance trajectory obtained at step 108 and the future risk map created at step 106 - Ono ¶67 & ¶122).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Ono teaches a vehicle motion control device capable of realizing optimum avoidance control in the case of an emergency.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a vehicle motion control device capable of realizing optimum avoidance control in the case of an emergency, as taught by Ono, with a reasonable expectation of success to improve the predication precision of the risk by correcting action predicated based on information of the road environment, weather and time zone, see Ono ¶109 for details.
As per claim 24
Flood further discloses wherein the operations comprise: detecting, by the self-driving device while navigating within the geographic area, an actionable condition; reporting, by the self-driving device, the actionable condition to a system controller configured to interact with the self-driving device and one or more other devices; and causing, by the system controller, the one or more other devices to perform operations that resolve the actionable condition (UAV 104 is also configured to communicate with mobile machines 108 to obtain sensor information sensed by sensors positioned on each of the machines, mobile machine action, as indicated at block 452, can include instructions to control mobile machine 108 to perform a ground disturbance correction…instructions to modify a prescribed travel route of machine 108, block 420 , ground disturbance correction logic 334 generates and outputs an indication of the corrective action selected to repair the particular sub-area – Flood ¶32 & ¶106 & ¶107).
As per claim 34
Flood does not specifically disclose wherein the operations comprise: obtaining, from data collected using one or more sensors, a terrain report specifying one or more obstacles that will interfere with the navigation of the self-driving device within the geographic area; generating, based on the terrain report, a navigation path that reduces the interference of the one or more obstacles with the navigation of the self-driving device within the geographic area; and causing the self-driving device to navigate within the geographic area according to the navigation path.
However, Ono teaches further comprising: obtaining, from data collected using one or more sensors, a terrain report specifying one or more obstacles that will interfere with the navigation of the self-driving device within the geographic area; generating, based on the terrain report, a navigation path that reduces the interference of the one or more obstacles with the navigation of the self-driving device within the geographic area; and causing the self-driving device to navigate within the geographic area according to the navigation path (group of sensors of the vehicle motion control device for detecting the external environment state, there are provided a camera 18, At next step 110, a risk at passage time TTC when the driver's vehicle passes through the shortest avoidance trajectory is created as a TTC risk map (passage time risk map), based on the passage time TTC on the shortest avoidance trajectory obtained at step 108 and the future risk map created at step 106 - Ono ¶67 & ¶122).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Ono teaches a vehicle motion control device capable of realizing optimum avoidance control in the case of an emergency.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a vehicle motion control device capable of realizing optimum avoidance control in the case of an emergency, as taught by Ono, with a reasonable expectation of success to improve the predication precision of the risk by correcting action predicated based on information of the road environment, weather and time zone, see Ono ¶109 for details.
As per claim 38
Flood further discloses wherein the operations comprise: detecting, by the self-driving device while navigating within the geographic area, an actionable condition; reporting, by the self-driving device, the actionable condition to a system controller configured to interact with the self-driving device and one or more other devices; and causing, by the system controller, the one or more other devices to perform operations that resolve the actionable condition (UAV 104 is also configured to communicate with mobile machines 108 to obtain sensor information sensed by sensors positioned on each of the machines, mobile machine action, as indicated at block 452, can include instructions to control mobile machine 108 to perform a ground disturbance correction…instructions to modify a prescribed travel route of machine 108, block 420 , ground disturbance correction logic 334 generates and outputs an indication of the corrective action selected to repair the particular sub-area – Flood ¶32 & ¶106 & ¶107).
Claims 6, 21, and 35 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, Jamison, and Ono, as per claims 5, 20, and 34, respectfully, and further in view of Sundarraj et al., US-20110035150-A1, hereinafter referred to as Sundarraj.
As per claim 6
Flood does not specifically disclose further comprising: retrieving the navigation path from a storage location after causing the self-driving device to navigate the geographic area; determining, based on an updated terrain report, that a different obstacle will currently interfere with the navigation of the self-driving device within the geographic area; generating, based on the updated terrain report, an updated navigation path that differs from the navigation path; and causing the self-driving device to navigate the geographic area according to the updated navigation path.
However, Sundarraj teaches further comprising: retrieving the navigation path from a storage location after causing the self-driving device to navigate the geographic area; determining, based on an updated terrain report, that a different obstacle will currently interfere with the navigation of the self-driving device within the geographic area; generating, based on the updated terrain report, an updated navigation path that differs from the navigation path; and causing the self-driving device to navigate the geographic area according to the updated navigation path (composite distance function map 28 will be updated as the vehicle 12 moves, and assuming that the vehicles 12 hold their current speed and direction, an estimate of the time for a potential collision between the vehicles 12 can be determined based on the dynamically changing distance contours provided by the composite distance function map 28 if such a potential for a collision exists. This information can then be used to provide warning signals or to take evasive action to prevent such a collision. - Sundarraj ¶19).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Sundarraj teaches a system and method for dynamically mapping the position and speed of objects around a vehicle for collision avoidance purposes.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a system and method for dynamically mapping the position and speed of objects around a vehicle for collision avoidance purposes, as taught by Sundarraj, with a reasonable expectation of success for collision avoidance purposes, see Sundarraj ¶7 for details.
As per claim 21
Flood does not specifically disclose wherein the operations comprise: retrieving the navigation path from a storage location after causing the self-driving device to navigate the geographic area; determining, based on an updated terrain report, that a different obstacle will currently interfere with the navigation of the self-driving device within the geographic area; generating, based on the updated terrain report, an updated navigation path that differs from the navigation path; and causing the self-driving device to navigate the geographic area according to the updated navigation path.
However, Sundarraj teaches wherein the operations comprise: retrieving the navigation path from a storage location after causing the self-driving device to navigate the geographic area; determining, based on an updated terrain report, that a different obstacle will currently interfere with the navigation of the self-driving device within the geographic area; generating, based on the updated terrain report, an updated navigation path that differs from the navigation path; and causing the self-driving device to navigate the geographic area according to the updated navigation path (composite distance function map 28 will be updated as the vehicle 12 moves, and assuming that the vehicles 12 hold their current speed and direction, an estimate of the time for a potential collision between the vehicles 12 can be determined based on the dynamically changing distance contours provided by the composite distance function map 28 if such a potential for a collision exists. This information can then be used to provide warning signals or to take evasive action to prevent such a collision. - Sundarraj ¶19).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Sundarraj teaches a system and method for dynamically mapping the position and speed of objects around a vehicle for collision avoidance purposes.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a system and method for dynamically mapping the position and speed of objects around a vehicle for collision avoidance purposes, as taught by Sundarraj, with a reasonable expectation of success for collision avoidance purposes, see Sundarraj ¶7 for details.
As per claim 35
Flood does not specifically disclose wherein the operations comprise: retrieving the navigation path from a storage location after causing the self-driving device to navigate the geographic area; determining, based on an updated terrain report, that a different obstacle will currently interfere with the navigation of the self-driving device within the geographic area; generating, based on the updated terrain report, an updated navigation path that differs from the navigation path; and causing the self-driving device to navigate the geographic area according to the updated navigation path.
However, Sundarraj teaches wherein the operations comprise: retrieving the navigation path from a storage location after causing the self-driving device to navigate the geographic area; determining, based on an updated terrain report, that a different obstacle will currently interfere with the navigation of the self-driving device within the geographic area; generating, based on the updated terrain report, an updated navigation path that differs from the navigation path; and causing the self-driving device to navigate the geographic area according to the updated navigation path (composite distance function map 28 will be updated as the vehicle 12 moves, and assuming that the vehicles 12 hold their current speed and direction, an estimate of the time for a potential collision between the vehicles 12 can be determined based on the dynamically changing distance contours provided by the composite distance function map 28 if such a potential for a collision exists. This information can then be used to provide warning signals or to take evasive action to prevent such a collision. - Sundarraj ¶19).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Sundarraj teaches a system and method for dynamically mapping the position and speed of objects around a vehicle for collision avoidance purposes.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a system and method for dynamically mapping the position and speed of objects around a vehicle for collision avoidance purposes, as taught by Sundarraj, with a reasonable expectation of success for collision avoidance purposes, see Sundarraj ¶7 for details.
Claims 7-8, 22-23, and 36-37 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, and Jamison, as per claims 3, 18, and 32, respectfully, and further in view of Stevens et al., US-20220215622-A1, and Asmari et al., US-20240190009-A1, hereinafter referred to as Stevens, and Asmari.
As per claim 7
Flood does not specifically disclose further comprising: analyzing the collected scan; selecting, based on the analyzing of the collected scan, installation locations for one or more of solar field components.
However, Stevens teaches further comprising: analyzing the collected scan; selecting, based on the analyzing of the collected scan, installation locations for one or more of solar field components (automated solar energy system design tool uses aerial imagery, 3D point clouds (e.g., LiDAR…to estimate the size and shape of a roof of a building and to determine the optimum location of the solar panels to maximize exposure to the sun, determining the optimal number of inverters and connection of solar panels to each other, Process 3500 includes the steps of: obtaining an aerial image - Stevens ¶20 & ¶113 & ¶142).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Stevens teaches an automated three-dimensional (3D) building model estimation system and method.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with an automated three-dimensional (3D) building model estimation system and method, as taught by Stevens, with a reasonable expectation of success to design an actual solar energy system that achieves the user's target energy savings goal and other user goals, see Stevens ¶6 for details.
Flood does not specifically disclose generating instructions that, upon execution, cause [[the]] one or more autonomous vehicles to transport the one or more solar field components to the selected installation locations for the one or more solar field components; and causing the one or more autonomous vehicles to transport the one or more solar field components to the selection installation locations for the one or more solar field components.
However, Asmari teaches generating instructions that, upon execution, cause [[the]] one or more autonomous vehicles to transport the one or more solar field components to the selected installation locations for the one or more solar field components; and causing the one or more autonomous vehicles to transport the one or more solar field components to the selection installation locations for the one or more solar field components (includes identifying an installation location for the first solar panel installation using a navigation module of the solar panel setting robot. The method also includes driving the one or more autonomous machines to the installation location using a drive module of the solar panel setting robot. The method further includes initiating an installation process, which includes sending a notification to a central controller using a communication module that the installation process has been initiated. The method includes retrieving a solar panel from the solar panel carrying robot using a robotic arm of the panel setting robot. The method also includes aligning the solar panel according to one or more parameters using a vision module. The method further includes fastening the solar panel to the bracket using one or more fasteners. - Asmari ¶11).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Asmari teaches a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines, as taught by Asmari, with a reasonable expectation of success to improve solar panel installation times and decrease installation costs, see Asmari ¶6 for details.
As per claim 8
Flood does not specifically disclose wherein selecting installation locations for one or more solar field components comprises selecting one or more of (i) installation locations for posts configured to support solar panels, (ii) inverters, (iii) transformers, (iv) service roads, or (v) a control station.
However, Asmari teaches wherein selecting installation locations for one or more solar field components comprises selecting one or more of (i) installation locations for posts configured to support solar panels, (ii) inverters, (iii) transformers, (iv) service roads, or (v) a control station (includes identifying an installation location for the first solar panel installation using a navigation module of the solar panel setting robot. The method also includes driving the one or more autonomous machines to the installation location using a drive module of the solar panel setting robot. The method further includes initiating an installation process, which includes sending a notification to a central controller using a communication module that the installation process has been initiated. The method includes retrieving a solar panel from the solar panel carrying robot using a robotic arm of the panel setting robot. The method also includes aligning the solar panel according to one or more parameters using a vision module. The method further includes fastening the solar panel to the bracket using one or more fasteners. - Asmari ¶11).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Asmari teaches a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines, as taught by Asmari, with a reasonable expectation of success to improve solar panel installation times and decrease installation costs, see Asmari ¶6 for details.
As per claim 22
Flood does not specifically disclose wherein the operations comprise: analyzing the collected scan; selecting, based on the analyzing of the collected scan, installation locations for one or more of solar field components.
However, Stevens teaches wherein the operations comprise analyzing the collected scan; selecting, based on the analyzing of the collected scan, installation locations for one or more of solar field components (automated solar energy system design tool uses aerial imagery, 3D point clouds (e.g., LiDAR…to estimate the size and shape of a roof of a building and to determine the optimum location of the solar panels to maximize exposure to the sun, determining the optimal number of inverters and connection of solar panels to each other, Process 3500 includes the steps of: obtaining an aerial image - Stevens ¶20 & ¶113 & ¶142).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Stevens teaches an automated three-dimensional (3D) building model estimation system and method.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with an automated three-dimensional (3D) building model estimation system and method, as taught by Stevens, with a reasonable expectation of success to design an actual solar energy system that achieves the user's target energy savings goal and other user goals, see Stevens ¶6 for details.
Flood does not specifically disclose generating instructions that, upon execution, cause one or more autonomous vehicles to transport the one or more solar field components to the selected installation locations for the one or more solar field components; and causing the one or more autonomous vehicles to transport the one or more solar field components to the selection installation locations for the one or more solar field components.
However, Asmari teaches generating instructions that, upon execution, cause one or more autonomous vehicles to transport the one or more solar field components to the selected installation locations for the one or more solar field components; and causing the one or more autonomous vehicles to transport the one or more solar field components to the selection installation locations for the one or more solar field components (includes identifying an installation location for the first solar panel installation using a navigation module of the solar panel setting robot. The method also includes driving the one or more autonomous machines to the installation location using a drive module of the solar panel setting robot. The method further includes initiating an installation process, which includes sending a notification to a central controller using a communication module that the installation process has been initiated. The method includes retrieving a solar panel from the solar panel carrying robot using a robotic arm of the panel setting robot. The method also includes aligning the solar panel according to one or more parameters using a vision module. The method further includes fastening the solar panel to the bracket using one or more fasteners. - Asmari ¶11).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Asmari teaches a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines, as taught by Asmari, with a reasonable expectation of success to improve solar panel installation times and decrease installation costs, see Asmari ¶6 for details.
As per claim 23
Flood does not specifically disclose wherein selecting installation locations for one or more solar field components comprises selecting one or more of (i) installation locations for posts configured to support solar panels, (ii) inverters, (iii) transformers, (iv) service roads, or (v) a control station.
However, Asmari teaches wherein selecting installation locations for one or more solar field components comprises selecting one or more of (i) installation locations for posts configured to support solar panels, (ii) inverters, (iii) transformers, (iv) service roads, or (v) a control station (includes identifying an installation location for the first solar panel installation using a navigation module of the solar panel setting robot. The method also includes driving the one or more autonomous machines to the installation location using a drive module of the solar panel setting robot. The method further includes initiating an installation process, which includes sending a notification to a central controller using a communication module that the installation process has been initiated. The method includes retrieving a solar panel from the solar panel carrying robot using a robotic arm of the panel setting robot. The method also includes aligning the solar panel according to one or more parameters using a vision module. The method further includes fastening the solar panel to the bracket using one or more fasteners. - Asmari ¶11).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Asmari teaches a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines, as taught by Asmari, with a reasonable expectation of success to improve solar panel installation times and decrease installation costs, see Asmari ¶6 for details.
As per claim 36
Flood does not specifically disclose wherein the operations comprise: analyzing the collected scan; selecting, based on the analyzing of the collected scan, installation locations for one or more of solar field components.
However, Stevens teaches wherein the operations comprise: analyzing the collected scan; selecting, based on the analyzing of the collected scan, installation locations for one or more of solar field components (automated solar energy system design tool uses aerial imagery, 3D point clouds (e.g., LiDAR…to estimate the size and shape of a roof of a building and to determine the optimum location of the solar panels to maximize exposure to the sun, determining the optimal number of inverters and connection of solar panels to each other, Process 3500 includes the steps of: obtaining an aerial image - Stevens ¶20 & ¶113 & ¶142).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Stevens teaches an automated three-dimensional (3D) building model estimation system and method.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with an automated three-dimensional (3D) building model estimation system and method, as taught by Stevens, with a reasonable expectation of success to design an actual solar energy system that achieves the user's target energy savings goal and other user goals, see Stevens ¶6 for details.
Flood does not specifically disclose generating instructions that, upon execution, cause one or more autonomous vehicles to transport the one or more solar field components to the selected installation locations for the one or more solar field components; and causing the one or more autonomous vehicles to transport the one or more solar field components to the selection installation locations for the one or more solar field components.
However, Asmari teaches generating instructions that, upon execution, cause one or more autonomous vehicles to transport the one or more solar field components to the selected installation locations for the one or more solar field components; and causing the one or more autonomous vehicles to transport the one or more solar field components to the selection installation locations for the one or more solar field components (includes identifying an installation location for the first solar panel installation using a navigation module of the solar panel setting robot. The method also includes driving the one or more autonomous machines to the installation location using a drive module of the solar panel setting robot. The method further includes initiating an installation process, which includes sending a notification to a central controller using a communication module that the installation process has been initiated. The method includes retrieving a solar panel from the solar panel carrying robot using a robotic arm of the panel setting robot. The method also includes aligning the solar panel according to one or more parameters using a vision module. The method further includes fastening the solar panel to the bracket using one or more fasteners. - Asmari ¶11).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Asmari teaches a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines, as taught by Asmari, with a reasonable expectation of success to improve solar panel installation times and decrease installation costs, see Asmari ¶6 for details.
As per claim 37
Flood does not specifically disclose wherein selecting installation locations for one or more solar field components comprises selecting one or more of (i) installation locations for posts configured to support solar panels, (ii) inverters, (iii) transformers, (iv) service roads, or (v) a control station.
However, Asmari teaches wherein selecting installation locations for one or more solar field components comprises selecting one or more of (i) installation locations for posts configured to support solar panels, (ii) inverters, (iii) transformers, (iv) service roads, or (v) a control station (includes identifying an installation location for the first solar panel installation using a navigation module of the solar panel setting robot. The method also includes driving the one or more autonomous machines to the installation location using a drive module of the solar panel setting robot. The method further includes initiating an installation process, which includes sending a notification to a central controller using a communication module that the installation process has been initiated. The method includes retrieving a solar panel from the solar panel carrying robot using a robotic arm of the panel setting robot. The method also includes aligning the solar panel according to one or more parameters using a vision module. The method further includes fastening the solar panel to the bracket using one or more fasteners. - Asmari ¶11).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Asmari teaches a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a system and method for installing solar panels using an advanced robotic system of one or more autonomous machines, as taught by Asmari, with a reasonable expectation of success to improve solar panel installation times and decrease installation costs, see Asmari ¶6 for details.
Claims 10, 25, and 39 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, Jamison, and Ono, as per claims 9, 24, and 38, respectfully, and further in view of Blanton, Jr. et al., US-12240449-B1, and Fox, hereinafter referred to as Blanton, Jr.
As per claim 10
Flood does not specifically disclose wherein: detecting the actionable condition comprises determining that vegetation is detected on a post of a solar panel.
However, Blanton, Jr teaches wherein: detecting the actionable condition comprises determining that vegetation is detected on a post of a solar panel (detection of objects in an operating site obscured by vegetation growth—in this example, the LIDAR data points corresponding to a solar panel and post and the vegetation obscuring a solar panel post, FIG. 6A for an autonomous mower to sense a solar farm for solar panels to determine the location of solar panel posts as well as determine if the solar panel itself is in an orientation that makes the solar panel an obstacle to the autonomous mower in removing vegetation growing close to the solar panel and its post, designed to provide for low profile mowing that can pass under solar panels even when the solar panels are positioned (or oriented) with at least one edge close to the ground - Blanton, Jr Column 3 Lines 33-37 & Column 3 Lines 51-59 & Column 10 Lines 60-63).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Blanton, Jr teaches an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles, as taught by Blanton, Jr, with a reasonable expectation of success for avoiding the dynamic object while navigating the autonomous vehicle to within the desired proximity of the stationary object, see Blanton, Jr Column 2 Lines 52-54 for details.
Flood does not specifically disclose causing the one or more other devices to perform operations that resolve the actionable condition comprises causing a vegetation mitigation device to navigate to a location of the post of the solar panel and remove or spray the vegetation.
However, Fox teaches causing the one or more other devices to perform operations that resolve the actionable condition comprises causing a vegetation mitigation device to navigate to a location of the post of the solar panel and remove or spray the vegetation (aerial vehicle 130 may be an unmanned aerial vehicle. For example, the aerial vehicle 130 may be four or six rotor drone…aerial vehicle 130 may include one or more cameras 132…aerial vehicle 130 may further include a flight path controller 138. The flight path controller 138 may communicate with the land analysis system 120 to receive flight path parameters…the land analysis system 120 itself could identify areas of interest based on the augmented reality view, and set and/or adjust flight parameters accordingly to modify the flight path of the aerial vehicle 130 in real-time, if one or more of the height…is less than one or more of the threshold height…AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130…transmit…a message…to perform the opposite operation…The AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 may also generate a notification for transmission to a user device 102 via the network 110 (e.g., a push notification) indicating that the plant (or group of plants) do not need to be pruned, the plant (or group of plants) should be pruned later than scheduled, and/or additional plants should be planted in the corresponding geographic area…the AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130 at the direction of a component of the land analysis system 120 can generate and transmit a message to cause the irrigation system 150 to water the plant (or group of plants) automatically, more frequently, and/or less frequently. - Fox Column 12 Line 27 – Column 13 Line 51 & Column 27 Line 35 – Column 27 Line 65).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Fox teaches a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site, as taught by Fox, with a reasonable expectation of success to estimate plant health, see Fox ¶44 for details.
As per claim 25
Flood does not specifically disclose wherein: detecting the actionable condition comprises determining that vegetation is detected on a post of a solar panel.
However, Blanton, Jr teaches wherein: detecting the actionable condition comprises determining that vegetation is detected on a post of a solar panel (detection of objects in an operating site obscured by vegetation growth—in this example, the LIDAR data points corresponding to a solar panel and post and the vegetation obscuring a solar panel post, FIG. 6A for an autonomous mower to sense a solar farm for solar panels to determine the location of solar panel posts as well as determine if the solar panel itself is in an orientation that makes the solar panel an obstacle to the autonomous mower in removing vegetation growing close to the solar panel and its post, designed to provide for low profile mowing that can pass under solar panels even when the solar panels are positioned (or oriented) with at least one edge close to the ground - Blanton, Jr Column 3 Lines 33-37 & Column 3 Lines 51-59 & Column 10 Lines 60-63).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Blanton, Jr teaches an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles, as taught by Blanton, Jr, with a reasonable expectation of success for avoiding the dynamic object while navigating the autonomous vehicle to within the desired proximity of the stationary object, see Blanton, Jr Column 2 Lines 52-54 for details.
Flood does not specifically disclose causing the one or more other devices to perform operations that resolve the actionable condition comprises causing a vegetation mitigation device to navigate to a location of the post of the solar panel and remove or spray the vegetation.
However, Fox teaches causing the one or more other devices to perform operations that resolve the actionable condition comprises causing a vegetation mitigation device to navigate to a location of the post of the solar panel and remove or spray the vegetation (aerial vehicle 130 may be an unmanned aerial vehicle. For example, the aerial vehicle 130 may be four or six rotor drone…aerial vehicle 130 may include one or more cameras 132…aerial vehicle 130 may further include a flight path controller 138. The flight path controller 138 may communicate with the land analysis system 120 to receive flight path parameters…the land analysis system 120 itself could identify areas of interest based on the augmented reality view, and set and/or adjust flight parameters accordingly to modify the flight path of the aerial vehicle 130 in real-time, if one or more of the height…is less than one or more of the threshold height…AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130…transmit…a message…to perform the opposite operation…The AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 may also generate a notification for transmission to a user device 102 via the network 110 (e.g., a push notification) indicating that the plant (or group of plants) do not need to be pruned, the plant (or group of plants) should be pruned later than scheduled, and/or additional plants should be planted in the corresponding geographic area…the AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130 at the direction of a component of the land analysis system 120 can generate and transmit a message to cause the irrigation system 150 to water the plant (or group of plants) automatically, more frequently, and/or less frequently. - Fox Column 12 Line 27 – Column 13 Line 51 & Column 27 Line 35 – Column 27 Line 65).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Fox teaches a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site, as taught by Fox, with a reasonable expectation of success to estimate plant health, see Fox ¶44 for details.
As per claim 39
Flood does not specifically disclose wherein: detecting the actionable condition comprises determining that vegetation is detected on a post of a solar panel.
However, Blanton, Jr teaches wherein: detecting the actionable condition comprises determining that vegetation is detected on a post of a solar panel (detection of objects in an operating site obscured by vegetation growth—in this example, the LIDAR data points corresponding to a solar panel and post and the vegetation obscuring a solar panel post, FIG. 6A for an autonomous mower to sense a solar farm for solar panels to determine the location of solar panel posts as well as determine if the solar panel itself is in an orientation that makes the solar panel an obstacle to the autonomous mower in removing vegetation growing close to the solar panel and its post, designed to provide for low profile mowing that can pass under solar panels even when the solar panels are positioned (or oriented) with at least one edge close to the ground - Blanton, Jr Column 3 Lines 33-37 & Column 3 Lines 51-59 & Column 10 Lines 60-63).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Blanton, Jr teaches an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles, as taught by Blanton, Jr, with a reasonable expectation of success for avoiding the dynamic object while navigating the autonomous vehicle to within the desired proximity of the stationary object, see Blanton, Jr Column 2 Lines 52-54 for details.
Flood does not specifically disclose causing the one or more other devices to perform operations that resolve the actionable condition comprises causing a vegetation mitigation device to navigate to a location of the post of the solar panel and remove or spray the vegetation.
However, Fox teaches causing the one or more other devices to perform operations that resolve the actionable condition comprises causing a vegetation mitigation device to navigate to a location of the post of the solar panel and remove or spray the vegetation (aerial vehicle 130 may be an unmanned aerial vehicle. For example, the aerial vehicle 130 may be four or six rotor drone…aerial vehicle 130 may include one or more cameras 132…aerial vehicle 130 may further include a flight path controller 138. The flight path controller 138 may communicate with the land analysis system 120 to receive flight path parameters…the land analysis system 120 itself could identify areas of interest based on the augmented reality view, and set and/or adjust flight parameters accordingly to modify the flight path of the aerial vehicle 130 in real-time, if one or more of the height…is less than one or more of the threshold height…AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130…transmit…a message…to perform the opposite operation…The AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 may also generate a notification for transmission to a user device 102 via the network 110 (e.g., a push notification) indicating that the plant (or group of plants) do not need to be pruned, the plant (or group of plants) should be pruned later than scheduled, and/or additional plants should be planted in the corresponding geographic area…the AI-based image processor 122, the plant strata identifier 123, and/or the plant health identifier 124 and/or the aerial vehicle 130 at the direction of a component of the land analysis system 120 can generate and transmit a message to cause the irrigation system 150 to water the plant (or group of plants) automatically, more frequently, and/or less frequently. - Fox Column 12 Line 27 – Column 13 Line 51 & Column 27 Line 35 – Column 27 Line 65).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Fox teaches a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a land analysis system that uses drone-captured images to detect plant health and/or soil moisture levels at a site, as taught by Fox, with a reasonable expectation of success to estimate plant health, see Fox ¶44 for details.
Claims 11, 26, and 40 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, Jamison, and Ono, as per claims 9, 24, and 38, respectfully, and further in view of DeLizio et al., US-20210064064-A1, hereinafter referred to as DeLizio.
As per claim 11
Flood does not specifically disclose wherein: detecting the actionable condition comprises detecting a characteristic of an object that is not accurately represented in a database storing characteristics of objects located in the geographic area; and causing the one or more other devices to perform operations that resolve the actional condition comprises updating the database storing characteristics of the objects located in the geographic area to reflect the detected characteristic of the object.
However, DeLizio teaches wherein: detecting the actionable condition comprises detecting a characteristic of an object that is not accurately represented in a database storing characteristics of objects located in the geographic area; and causing the one or more other devices to perform operations that resolve the actional condition comprises updating the database storing characteristics of the objects located in the geographic area to reflect the detected characteristic of the object (block 802, a video processor receives a video content stream that was captured by an aerial autonomous vehicle, block 804, the video processor determines information about objects in the video content stream. For example, the video processor may identify objects (e.g., determine that an object is a vehicle, person, etc.), track object movement, determine object location, block 1404, the control data server updates information about objects in the control data stream. For example, if object information received from autonomous vehicles indicates that a particular object was assigned an incorrect object type, the control data server updates the object type - DeLizio ¶76 & ¶77 & ¶113).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. DeLizio teaches a method for providing control information to autonomous vehicles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a method for providing control information to autonomous vehicles, as taught by DeLizio, with a reasonable expectation of success to determine a path avoiding the object, see DeLizio ¶100 for details.
As per claim 26
Flood does not specifically disclose wherein: detecting the actionable condition comprises detecting a characteristic of an object that is not accurately represented in a database storing characteristics of objects located in the geographic area; and causing the one or more other devices to perform operations that resolve the actional condition comprises updating the database storing characteristics of the objects located in the geographic area to reflect the detected characteristic of the object.
However, DeLizio teaches wherein: detecting the actionable condition comprises detecting a characteristic of an object that is not accurately represented in a database storing characteristics of objects located in the geographic area; and causing the one or more other devices to perform operations that resolve the actional condition comprises updating the database storing characteristics of the objects located in the geographic area to reflect the detected characteristic of the object (block 802, a video processor receives a video content stream that was captured by an aerial autonomous vehicle, block 804, the video processor determines information about objects in the video content stream. For example, the video processor may identify objects (e.g., determine that an object is a vehicle, person, etc.), track object movement, determine object location, block 1404, the control data server updates information about objects in the control data stream. For example, if object information received from autonomous vehicles indicates that a particular object was assigned an incorrect object type, the control data server updates the object type - DeLizio ¶76 & ¶77 & ¶113).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. DeLizio teaches a method for providing control information to autonomous vehicles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a method for providing control information to autonomous vehicles, as taught by DeLizio, with a reasonable expectation of success to determine a path avoiding the object, see DeLizio ¶100 for details.
As per claim 40
Flood does not specifically disclose wherein: detecting the actionable condition comprises detecting a characteristic of an object that is not accurately represented in a database storing characteristics of objects located in the geographic area; and causing the one or more other devices to perform operations that resolve the actional condition comprises updating the database storing characteristics of the objects located in the geographic area to reflect the detected characteristic of the object.
However, DeLizio teaches wherein: detecting the actionable condition comprises detecting a characteristic of an object that is not accurately represented in a database storing characteristics of objects located in the geographic area; and causing the one or more other devices to perform operations that resolve the actional condition comprises updating the database storing characteristics of the objects located in the geographic area to reflect the detected characteristic of the object (block 802, a video processor receives a video content stream that was captured by an aerial autonomous vehicle, block 804, the video processor determines information about objects in the video content stream. For example, the video processor may identify objects (e.g., determine that an object is a vehicle, person, etc.), track object movement, determine object location, block 1404, the control data server updates information about objects in the control data stream. For example, if object information received from autonomous vehicles indicates that a particular object was assigned an incorrect object type, the control data server updates the object type - DeLizio ¶76 & ¶77 & ¶113).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. DeLizio teaches a method for providing control information to autonomous vehicles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a method for providing control information to autonomous vehicles, as taught by DeLizio, with a reasonable expectation of success to determine a path avoiding the object, see DeLizio ¶100 for details.
Claims 12, 27, and 41 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, Jamison, Ono, and DeLizio, as per claims 9, 26, and 40, respectfully, and further in view of Michini et al., US-20180003656-A1, hereinafter referred to as Michini.
As per claim 12
Flood does not specifically disclose wherein: detecting the actionable condition comprises detecting one or more of (i) an out of tolerance temperature reading on a solar panel, (ii) burn marks, (iii) electrical arcing, (iv) a crack in a solar panel, or (v) a ground fault that has not caused a solar panel failure condition; and causing the one or more other devices to perform operations that resolve the actional condition comprises causing the one or more other devices to perform one or more of (i) generating a visible or audible alarm, (ii) navigate a vehicle to a location of the actionable condition, or (iii) disabling the solar panel.
However, Michini teaches wherein: detecting the actionable condition comprises detecting one or more of (i) an out of tolerance temperature reading on a solar panel, (ii) burn marks, (iii) electrical arcing, (iv) a crack in a solar panel, or (v) a ground fault that has not caused a solar panel failure condition; and causing the one or more other devices to perform operations that resolve the actional condition comprises causing the one or more other devices to perform one or more of (i) generating a visible or audible alarm, (ii) navigate a vehicle to a location of the actionable condition, or (iii) disabling the solar panel (UAV 302 or the server can determine respective temperatures of solar cells in solar panel 304 from the thermal maps 308. Based on the respective temperatures, UAV 302 or the server can determine whether any solar cell is overheating. UAV 302 or the server can then determine whether any solar cell, or solar panel 304 as a whole, is working according to specification, or has failed. In the example shown, UAV 302 or the server can determine whether one or more cells, e.g., cell 310, is overheating. UAV 302 or the server can estimate a cause of failure of cell 310 or of solar panel 304, and generate a report on the failure and the cause, In report generation stage 614, the server can generate a report including the images, the analysis, and the annotations - Michini ¶67 & ¶92).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Michini teaches methods, systems, and program products for inspecting solar panels using unmanned aerial vehicles (UAVs).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with methods, systems, and program products for inspecting solar panels using unmanned aerial vehicles (UAVs), as taught by Michini, with a reasonable expectation of success to help identify mismatched panels where higher performing modules are impeded by lower performing modules, see Michini ¶7 for details.
As per claim 27
Flood does not specifically disclose wherein: detecting the actionable condition comprises detecting one or more of (i) an out of tolerance temperature reading on a solar panel, (ii) burn marks, (iii) electrical arcing, (iv) a crack in a solar panel, or (v) a ground fault that has not caused a solar panel failure condition; and causing the one or more other devices to perform operations that resolve the actional condition comprises causing the one or more other devices to perform one or more of (i) generating a visible or audible alarm, (ii) navigate a vehicle to a location of the actionable condition, or (iii) disabling the solar panel.
However, Michini teaches wherein: detecting the actionable condition comprises detecting one or more of (i) an out of tolerance temperature reading on a solar panel, (ii) burn marks, (iii) electrical arcing, (iv) a crack in a solar panel, or (v) a ground fault that has not caused a solar panel failure condition; and causing the one or more other devices to perform operations that resolve the actional condition comprises causing the one or more other devices to perform one or more of (i) generating a visible or audible alarm, (ii) navigate a vehicle to a location of the actionable condition, or (iii) disabling the solar panel (UAV 302 or the server can determine respective temperatures of solar cells in solar panel 304 from the thermal maps 308. Based on the respective temperatures, UAV 302 or the server can determine whether any solar cell is overheating. UAV 302 or the server can then determine whether any solar cell, or solar panel 304 as a whole, is working according to specification, or has failed. In the example shown, UAV 302 or the server can determine whether one or more cells, e.g., cell 310, is overheating. UAV 302 or the server can estimate a cause of failure of cell 310 or of solar panel 304, and generate a report on the failure and the cause, In report generation stage 614, the server can generate a report including the images, the analysis, and the annotations - Michini ¶67 & ¶92).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Michini teaches methods, systems, and program products for inspecting solar panels using unmanned aerial vehicles (UAVs).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with methods, systems, and program products for inspecting solar panels using unmanned aerial vehicles (UAVs), as taught by Michini, with a reasonable expectation of success to help identify mismatched panels where higher performing modules are impeded by lower performing modules, see Michini ¶7 for details.
As per claim 41
Flood does not specifically disclose wherein: detecting the actionable condition comprises detecting one or more of (i) an out of tolerance temperature reading on a solar panel, (ii) burn marks, (iii) electrical arcing, (iv) a crack in a solar panel, or (v) a ground fault that has not caused a solar panel failure condition; and causing the one or more other devices to perform operations that resolve the actional condition comprises causing the one or more other devices to perform one or more of (i) generating a visible or audible alarm, (ii) navigate a vehicle to a location of the actionable condition, or (iii) disabling the solar panel.
However, Michini teaches wherein: detecting the actionable condition comprises detecting one or more of (i) an out of tolerance temperature reading on a solar panel, (ii) burn marks, (iii) electrical arcing, (iv) a crack in a solar panel, or (v) a ground fault that has not caused a solar panel failure condition; and causing the one or more other devices to perform operations that resolve the actional condition comprises causing the one or more other devices to perform one or more of (i) generating a visible or audible alarm, (ii) navigate a vehicle to a location of the actionable condition, or (iii) disabling the solar panel (UAV 302 or the server can determine respective temperatures of solar cells in solar panel 304 from the thermal maps 308. Based on the respective temperatures, UAV 302 or the server can determine whether any solar cell is overheating. UAV 302 or the server can then determine whether any solar cell, or solar panel 304 as a whole, is working according to specification, or has failed. In the example shown, UAV 302 or the server can determine whether one or more cells, e.g., cell 310, is overheating. UAV 302 or the server can estimate a cause of failure of cell 310 or of solar panel 304, and generate a report on the failure and the cause, In report generation stage 614, the server can generate a report including the images, the analysis, and the annotations - Michini ¶67 & ¶92).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Michini teaches methods, systems, and program products for inspecting solar panels using unmanned aerial vehicles (UAVs).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with methods, systems, and program products for inspecting solar panels using unmanned aerial vehicles (UAVs), as taught by Michini, with a reasonable expectation of success to help identify mismatched panels where higher performing modules are impeded by lower performing modules, see Michini ¶7 for details.
Claims 13, 28, and 42 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, as per claims 1, 15, and 30, respectfully, and further in view of Freeman et al., US-20100193261-A1, hereinafter referred to as Freeman.
As per claim 13
Flood does not specifically disclose further comprising: monitoring a location of the given device within the geographic area; remotely adjusting, using one or more optical or electrical control signals, orientations of one or more objects within the geographic area to prevent navigation of the given device from being impeded as the given device approaches locations of the one or more objects.
However, Freeman teaches further comprising: monitoring a location of the given device within the geographic area; remotely adjusting, using one or more optical or electrical control signals, orientations of one or more objects within the geographic area to prevent navigation of the given device from being impeded as the given device approaches locations of the one or more objects (FIG. 6 is a cutaway view of the side of the vehicle which features a solar array 50 so large that it must be retracted while the vehicle is driving in order to avoid hitting other vehicles…FIG. 44 depicts the area occupied by the mechanism or hydraulic system that raises and lowers the inner tube 48…When it is in its normal deployed position as pictured in FIG. 6, the way oversized solar array 50 can be a few feet above the top of the vehicle so that the extended array won't hit nearby parked cars or people
- Freeman ¶84).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Freeman teaches a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath, as taught by Freeman, with a reasonable expectation of success to maximize power generation while avoiding hitting people, objects or other vehicles, see Freeman ¶27 for details.
As per claim 28
Flood does not specifically disclose wherein the operations comprise: monitoring a location of the given device within the geographic area; remotely adjusting, using one or more optical or electrical control signals, orientations of one or more objects within the geographic area to prevent navigation of the given device from being impeded as the given device approaches locations of the one or more objects.
However, Freeman teaches wherein the operations comprise: monitoring a location of the given device within the geographic area; remotely adjusting, using one or more optical or electrical control signals, orientations of one or more objects within the geographic area to prevent navigation of the given device from being impeded as the given device approaches locations of the one or more objects (FIG. 6 is a cutaway view of the side of the vehicle which features a solar array 50 so large that it must be retracted while the vehicle is driving in order to avoid hitting other vehicles…FIG. 44 depicts the area occupied by the mechanism or hydraulic system that raises and lowers the inner tube 48…When it is in its normal deployed position as pictured in FIG. 6, the way oversized solar array 50 can be a few feet above the top of the vehicle so that the extended array won't hit nearby parked cars or people
- Freeman ¶84).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Freeman teaches a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath, as taught by Freeman, with a reasonable expectation of success to maximize power generation while avoiding hitting people, objects or other vehicles, see Freeman ¶27 for details.
As per claim 42
Flood does not specifically disclose wherein the operations comprise: monitoring a location of the given device within the geographic area; remotely adjusting, using one or more optical or electrical control signals, orientations of one or more objects within the geographic area to prevent navigation of the given device from being impeded as the given device approaches locations of the one or more objects.
However, Freeman teaches wherein the operations comprise: monitoring a location of the given device within the geographic area; remotely adjusting, using one or more optical or electrical control signals, orientations of one or more objects within the geographic area to prevent navigation of the given device from being impeded as the given device approaches locations of the one or more objects (FIG. 6 is a cutaway view of the side of the vehicle which features a solar array 50 so large that it must be retracted while the vehicle is driving in order to avoid hitting other vehicles…FIG. 44 depicts the area occupied by the mechanism or hydraulic system that raises and lowers the inner tube 48…When it is in its normal deployed position as pictured in FIG. 6, the way oversized solar array 50 can be a few feet above the top of the vehicle so that the extended array won't hit nearby parked cars or people
- Freeman ¶84).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Freeman teaches a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath, as taught by Freeman, with a reasonable expectation of success to maximize power generation while avoiding hitting people, objects or other vehicles, see Freeman ¶27 for details.
Claims 14, 29, and 43 are rejected under 35 U.S.C. § 103 as being unpatentable over Flood, and Freeman, as per claims 13, 28, and 42, respectfully, and further in view of Blanton, Jr.
As per claim 14
Flood does not specifically disclose wherein adjusting orientations of one or more objects comprises adjusting a tilt angle of a solar panel to an angle that enables [vehicles to navigate without striking the solar panel].
However, Freeman teaches wherein adjusting orientations of one or more objects comprises adjusting a tilt angle of a solar panel to an angle that enables [vehicles to navigate without striking the solar panel] (FIG. 6 is a cutaway view of the side of the vehicle which features a solar array 50 so large that it must be retracted while the vehicle is driving in order to avoid hitting other vehicles…FIG. 44 depicts the area occupied by the mechanism or hydraulic system that raises and lowers the inner tube 48…When it is in its normal deployed position as pictured in FIG. 6, the way oversized solar array 50 can be a few feet above the top of the vehicle so that the extended array won't hit nearby parked cars or people
- Freeman ¶84).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Freeman teaches a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath, as taught by Freeman, with a reasonable expectation of success to maximize power generation while avoiding hitting people, objects or other vehicles, see Freeman ¶27 for details.
Flood does not specifically disclose the given device to navigate under the solar panel.
However, Blanton, Jr teaches the given device to navigate under the solar panel (detection of objects in an operating site obscured by vegetation growth—in this example, the LIDAR data points corresponding to a solar panel and post and the vegetation obscuring a solar panel post, FIG. 6A for an autonomous mower to sense a solar farm for solar panels to determine the location of solar panel posts as well as determine if the solar panel itself is in an orientation that makes the solar panel an obstacle to the autonomous mower in removing vegetation growing close to the solar panel and its post, designed to provide for low profile mowing that can pass under solar panels even when the solar panels are positioned (or oriented) with at least one edge close to the ground - Blanton, Jr Column 3 Lines 33-37 & Column 3 Lines 51-59 & Column 10 Lines 60-63).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Blanton, Jr teaches an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles, as taught by Blanton, Jr, with a reasonable expectation of success for avoiding the dynamic object while navigating the autonomous vehicle to within the desired proximity of the stationary object, see Blanton, Jr Column 2 Lines 52-54 for details.
As per claim 29
Flood does not specifically disclose wherein adjusting orientations of one or more objects comprises adjusting a tilt angle of a solar panel to an angle that enables [vehicles to navigate without striking the solar panel].
However, Freeman teaches wherein adjusting orientations of one or more objects comprises adjusting a tilt angle of a solar panel to an angle that enables [vehicles to navigate without striking the solar panel] (FIG. 6 is a cutaway view of the side of the vehicle which features a solar array 50 so large that it must be retracted while the vehicle is driving in order to avoid hitting other vehicles…FIG. 44 depicts the area occupied by the mechanism or hydraulic system that raises and lowers the inner tube 48…When it is in its normal deployed position as pictured in FIG. 6, the way oversized solar array 50 can be a few feet above the top of the vehicle so that the extended array won't hit nearby parked cars or people
- Freeman ¶84).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Freeman teaches a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath, as taught by Freeman, with a reasonable expectation of success to maximize power generation while avoiding hitting people, objects or other vehicles, see Freeman ¶27 for details.
Flood does not specifically disclose the given device to navigate under the solar panel.
However, Blanton, Jr teaches the given device to navigate under the solar panel (detection of objects in an operating site obscured by vegetation growth—in this example, the LIDAR data points corresponding to a solar panel and post and the vegetation obscuring a solar panel post, FIG. 6A for an autonomous mower to sense a solar farm for solar panels to determine the location of solar panel posts as well as determine if the solar panel itself is in an orientation that makes the solar panel an obstacle to the autonomous mower in removing vegetation growing close to the solar panel and its post, designed to provide for low profile mowing that can pass under solar panels even when the solar panels are positioned (or oriented) with at least one edge close to the ground - Blanton, Jr Column 3 Lines 33-37 & Column 3 Lines 51-59 & Column 10 Lines 60-63).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Blanton, Jr teaches an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles, as taught by Blanton, Jr, with a reasonable expectation of success for avoiding the dynamic object while navigating the autonomous vehicle to within the desired proximity of the stationary object, see Blanton, Jr Column 2 Lines 52-54 for details.
As per claim 43
Flood does not specifically disclose wherein adjusting orientations of one or more objects comprises adjusting a tilt angle of a solar panel to an angle that enables [vehicles to navigate without striking the solar panel].
However, Freeman teaches wherein adjusting orientations of one or more objects comprises adjusting a tilt angle of a solar panel to an angle that enables [vehicles to navigate without striking the solar panel] (FIG. 6 is a cutaway view of the side of the vehicle which features a solar array 50 so large that it must be retracted while the vehicle is driving in order to avoid hitting other vehicles…FIG. 44 depicts the area occupied by the mechanism or hydraulic system that raises and lowers the inner tube 48…When it is in its normal deployed position as pictured in FIG. 6, the way oversized solar array 50 can be a few feet above the top of the vehicle so that the extended array won't hit nearby parked cars or people
- Freeman ¶84).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Freeman teaches a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with a tiltable solar panel than can be repositioned to avoid colliding with passing vehicles traveling underneath, as taught by Freeman, with a reasonable expectation of success to maximize power generation while avoiding hitting people, objects or other vehicles, see Freeman ¶27 for details.
Flood does not specifically disclose the given device to navigate under the solar panel.
However, Blanton, Jr teaches the given device to navigate under the solar panel (detection of objects in an operating site obscured by vegetation growth—in this example, the LIDAR data points corresponding to a solar panel and post and the vegetation obscuring a solar panel post, FIG. 6A for an autonomous mower to sense a solar farm for solar panels to determine the location of solar panel posts as well as determine if the solar panel itself is in an orientation that makes the solar panel an obstacle to the autonomous mower in removing vegetation growing close to the solar panel and its post, designed to provide for low profile mowing that can pass under solar panels even when the solar panels are positioned (or oriented) with at least one edge close to the ground - Blanton, Jr Column 3 Lines 33-37 & Column 3 Lines 51-59 & Column 10 Lines 60-63).
Flood discloses the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations. Blanton, Jr teaches an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Flood, systems and methods for the use of drones in improving performance and data analysis for forestry applications within a variety of worksite operations, with an autonomous vehicle that detects and determines in real-time dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles, as taught by Blanton, Jr, with a reasonable expectation of success for avoiding the dynamic object while navigating the autonomous vehicle to within the desired proximity of the stationary object, see Blanton, Jr Column 2 Lines 52-54 for details.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FARIS ASIM SHAIKH whose telephone number is (571)272-6426. The examiner can normally be reached 8:00-5:30 M-F EST.
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/F.A.S./Examiner, Art Unit 3668
/Fadey S. Jabr/Supervisory Patent Examiner, Art Unit 3668
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