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 .
This is a Final Action on the Merits. Claims 1-2, 5-8, 10-11, 13-14, 16-17, and 19-26 are currently pending and are addressed below.
Election/Restrictions
Applicant’s election with traverse of Invention I (Claims 1-2, 5-8, 10, and 19-23 in the reply filed on January 21st, 2026 in response to the Office Action dated January 12th, 2026 is acknowledged. The Applicant states (Amend. 2-3) that there is not a not a serious search burden. The examiner respectfully disagrees. As discussed in the Office Action dated January 12th, 2026, the inventions require divergent search terminology for a determination of the “monitoring location” as required for each Invention. Therefore. Claims 1-2, 5-8, 10, and 19-23 are currently pending and are examined below. Claims 11, 13-14, 16-17, and 24-26 have been withdrawn from consideration.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on October 7th, 2025 October 22nd, 2025, November 3rd, 2025, November 17th, 2025, December 4th, 2025 have been considered and entered.
Response to Amendment
The preliminary amendment filed on January 21st, 2026 has been considered and entered. Accordingly, claims 1, 5-8, 10-11, 13-14, 16-17, and 19-20 have been amended. Claims 3-4, 9, 12, 15, and 18 have been cancelled. Claims 21-26 have been newly added.
Response to Arguments
The previous rejection of Claims 1-2, 5-8, 10, and 19-23 under 35 USC 101 have been overcome due to the Applicant’s Amendments.
The Applicant’s Arguments with respect to claims 1-2, 5-8, 10, and 19-23 have been considered but are moot in view of the newly formulated grounds of rejection necessitated by the Applicant’s Amendments.
Claim Rejections - 35 USC § 103
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 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 5-6, 8, 10, and 21-23 are rejected under 35 U.S.C. 103 as being unpatentable over Sugumaran (US 20170031365 A1) (“Sugumaran”) in view of Shekar (US 20210146977 A1) (“Shekar”) in view of Meyer (US 20120029732 A1) (“Meyer”).
.
With respect to claim 1, Sugumaran teaches an agricultural system comprising:
a sensor system disposed on a drone communicably coupled to and remotely positionable from an agricultural work machine at a worksite, the sensor system configured to detect one or more attributes1 in a measurement area ahead of the agricultural work machine, relative to a travel direction of the agricultural work machine, and generate sensor data indicative of the detected one or more attributes in the measurement area ahead of the agricultural work machine (See at least Sugumaran FIG. 4 and Paragraph 46 “UAV 152 thus first uses its one or more attribute sensors 112 to sense an attribute of an area of the worksite that is forward of the mobile crop care machine 102, as machine 102 is traveling in the forward direction. This is indicated by block 166 in FIG. 4. In doing so, UAV 104 can correlate the attribute signal with a position from which it is sensed, as indicated by positioning system 116.”);
one or more processors; and memory storing instructions, executable by the one or more processors, that, when executed by the one or more processors, cause the one or more processors to:
identify a travel speed of the agricultural work machine (See at least Sugumaran Paragraph 15);
identify a latency of the agricultural work machine (See at least Sugumaran Paragraph 37).
Sugumaran, however, fails to explicitly disclose to identify a monitoring location based. at least in part, on the identified travel speed of the agricultural work machine and the identified latency of the agricultural work machine, the monitoring location defining a location to position the drone to have the sensor system, disposed on the drone. detect the one or more attributes in the measurement area ahead of the agricultural work machine: generate a travel plan for the drone, the travel plan including the monitoring location; and control travel of the drone based on the travel plan.
Shekar teaches to identify a monitoring location based. at least in part, on the identified travel speed of the agricultural work machine and the identified latency of the agricultural work machine, the monitoring location defining a location to position the drone to have the sensor system, disposed on the drone (See at least Rajan Paragraph 28 “leading distance 36. In some embodiments, leading distance 36 is no less than braking distance 26. In other embodiments, leading distance 36 is greater than braking distance 26 to account for the processing overhead needed for the detection and classification of a hazardous condition at drone 20, as well as to account for the time needed for transmission of the information from drone 20 to monitored vehicle 22. Drone 20 is configured to detect hazardous conditions ahead of drone 20 and use a wireless communication link 38 to notify monitored vehicle 22 of the hazardous condition so that monitored vehicle 22 can take appropriate corrective action (e.g., initiate braking).” | Paragraphs 34-35 “Processing unit 42, executing monitoring module 60, may be further configured to determine leading distance 36 for drone 20 based on the determined braking distance 26. As discussed above, leading distance 36 is no less than braking distance 26 and may be greater than braking distance 26 to account for the overhead needed for the processing and communicating operations. In some embodiments, adaptive speed control unit 44 manages navigation control operations for drone 20. For example, adaptive speed control unit 44 is configured to adjust a guide speed and position of drone 20 by controlling operation of motors and actuators (not shown) of drone 20 such that drone 20 travels ahead of monitored vehicle 22 by at least leading distance 36. The motors may be used for rotation of propellers and the actuators may be used for navigation surface control such as ailerons, rudders, flaps, landing gear, and so forth. As will be discussed in significantly greater detail in connection with FIG. 4, processing unit 42 may be configured to determine another braking distance for monitored vehicle 22 in response to a change in current speed 62 of monitored vehicle 22 and determine an updated leading distance 36 based on the change in current speed. Accordingly, adaptive speed control unit 44 may adjust the guide speed and position of drone 20 such that drone 20 travels ahead of monitored vehicle 22 by at least the updated leading distance.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Sugumaran to identify a monitoring location based. at least in part, on the identified travel speed of the agricultural work machine and the identified latency of the agricultural work machine, the monitoring location defining a location to position the drone to have the sensor system, disposed on the drone, as taught by Shekar as disclosed above, in order to ensure an optimal distance for the drone to monitor any changes in the environment of the vehicle (Shekar Paragraph 1 “More specifically, the present invention relates to real time autonomous positioning and navigation of an unmanned vehicle ahead of a monitored moving vehicle for detecting hazardous conditions and for enhancing operational efficiency.”).
Sugumaran in view or Shekar fail to explicitly disclose the monitoring location defining a location to position the drone to have the sensor system, disposed on the drone. detect the one or more attributes in the measurement area ahead of the agricultural work machine: generate a travel plan for the drone, the travel plan including the monitoring location; and control travel of the drone based on the travel plan.
Meyer, however, teaches that the monitoring location defining a location to position the drone to have the sensor system, disposed on the drone. detect the one or more attributes in the measurement area ahead of the agricultural work machine: generate a travel plan for the drone, the travel plan including the monitoring location; and control travel of the drone based on the travel plan (See at least Meyer Paragraph 16 “The signals of the sensor can also be used by the control unit for planning a route of the harvester. For this purpose, it is preferred that the aircraft initially flies over and maps the field from a sufficient height (i.e., a greater height than during harvesting) in order to prepare the route plan. This makes it possible to drive around immovable obstacles (such as larger rocks) or movable obstacles (e.g., animals) or areas of a field that are not suitable for harvesting, such as, e.g., waterholes with dense weed cover, or to stop the harvester in order to avoid a collision. The aircraft can also be used during the drive to the field in order to detect obstacles in advance and to drive around these obstacles (e.g., passages with insufficient height or width or severe roadway damage). In this case, only the aircraft may initially fly over and explore the planned driving route. Crop parameters determined by the sensor of the aircraft such as, for example, the plant size, the level of maturity, the moisture, the protein content, etc., can also be taken into account during the preparation of the route plan in order to collect largely homogenous (or well mixed) crop qualities in the individual load containers.” | Paragraphs 36-38 “During the harvesting process, the control unit 112 transmits data with respect to the current position of the harvester 10 to the flight control 170 via the interface 90, the receiving and transmitting device 92 and the transmitting and receiving unit 166. The flight control controls the aircraft 150 in such a way that it is always positioned at a constant height of a few meters above the harvester 10, namely slightly in front of the ejecting end of the discharging device 40 in the forward direction and between the harvester 10 and the transport vehicle 12 in the lateral direction … The harvester 10 is steered based on the signals of the sensor 156 that contain information on the position of the crop edge 54. They are merged with signals of the aforementioned sensor for determining the position of sensing bands 62 arranged at the divider point of the harvesting header 28, namely with consideration of the different measured positions of the crop edge 54 in the forward direction, and serve for controlling the steering device 114.”).
It would have been obvious to one of ordinary skill in the art to have modified the system of Sugumaran in view of Shekar to include that the monitoring location defining a location to position the drone to have the sensor system, disposed on the drone. detect the one or more attributes in the measurement area ahead of the agricultural work machine: generate a travel plan for the drone, the travel plan including the monitoring location; and control travel of the drone based on the travel plan, as taught by Meyer, in order ensure efficient preparation of the route for the agricultural work machine (Meyer Paragraph 8 “In one embodiment, a control unit is designed such that it controls an actuator for influencing an operating parameter of the harvester and/or the transport vehicle in real time based on signals of the sensor in the harvesting mode.”).
With respect to claim 2, Sugumaran in view of Shekar in view of Meyer teaches that the one or more attributes comprise at least one of a plant attribute or an environmental attribute (See at least Sugumaran Paragraph 34 “Attribute sensors 112 illustratively sense one or more attributes of a field or a crop over which machine 102 is traveling. For instance, attribute sensors 112 can sense such things as soil, soil type, soil moisture, soil cover, residue density, crop type, weed presence and weed type, plant size, plant height, plant health, plant vigor, chemical presence, chemical distribution, etc. Sensors 112 can thus be a wide variety of different types of sensors, such as cameras, infrared cameras or other infrared sensors, video cameras, stereo cameras, LIDAR sensors, structured light systems, etc.”).
With respect to claim 5, Sugumaran in view of Shekar in view of Meyer teaches to identify one or more characteristics of an obstruction at a worksite, the one or more characteristics comprising one or more of a location of the obstruction or a future location of the obstruction; and generate the travel plan based, at least in part, on the identified one or more characteristics of the obstruction (See at least Meyer Paragraph 16 “The signals of the sensor can also be used by the control unit for planning a route of the harvester. For this purpose, it is preferred that the aircraft initially flies over and maps the field from a sufficient height (i.e., a greater height than during harvesting) in order to prepare the route plan. This makes it possible to drive around immovable obstacles (such as larger rocks) or movable obstacles (e.g., animals) or areas of a field that are not suitable for harvesting, such as, e.g., waterholes with dense weed cover, or to stop the harvester in order to avoid a collision. The aircraft can also be used during the drive to the field in order to detect obstacles in advance and to drive around these obstacles (e.g., passages with insufficient height or width or severe roadway damage). In this case, only the aircraft may initially fly over and explore the planned driving route. Crop parameters determined by the sensor of the aircraft such as, for example, the plant size, the level of maturity, the moisture, the protein content, etc., can also be taken into account during the preparation of the route plan in order to collect largely homogenous (or well mixed) crop qualities in the individual load containers.”).
With respect to claim 6, Sugumaran in view of Shekar in view of Meyer teaches to identify the monitoring location, based, at least in part, on the identified one or more characteristics of the obstruction, the identified monitoring location further defining a location to position the drone such that the obstruction does not obstruct the sensor system from detecting the one or more attributes in the measurement area ahead of the agricultural work machine. (See at least Meyer Paragraph 16 “The signals of the sensor can also be used by the control unit for planning a route of the harvester. For this purpose, it is preferred that the aircraft initially flies over and maps the field from a sufficient height (i.e., a greater height than during harvesting) in order to prepare the route plan. This makes it possible to drive around immovable obstacles (such as larger rocks) or movable obstacles (e.g., animals) or areas of a field that are not suitable for harvesting, such as, e.g., waterholes with dense weed cover, or to stop the harvester in order to avoid a collision. The aircraft can also be used during the drive to the field in order to detect obstacles in advance and to drive around these obstacles (e.g., passages with insufficient height or width or severe roadway damage). In this case, only the aircraft may initially fly over and explore the planned driving route. Crop parameters determined by the sensor of the aircraft such as, for example, the plant size, the level of maturity, the moisture, the protein content, etc., can also be taken into account during the preparation of the route plan in order to collect largely homogenous (or well mixed) crop qualities in the individual load containers.” | Paragraphs 36-38 “During the harvesting process, the control unit 112 transmits data with respect to the current position of the harvester 10 to the flight control 170 via the interface 90, the receiving and transmitting device 92 and the transmitting and receiving unit 166. The flight control controls the aircraft 150 in such a way that it is always positioned at a constant height of a few meters above the harvester 10, namely slightly in front of the ejecting end of the discharging device 40 in the forward direction and between the harvester 10 and the transport vehicle 12 in the lateral direction … The harvester 10 is steered based on the signals of the sensor 156 that contain information on the position of the crop edge 54. They are merged with signals of the aforementioned sensor for determining the position of sensing bands 62 arranged at the divider point of the harvesting header 28, namely with consideration of the different measured positions of the crop edge 54 in the forward direction, and serve for controlling the steering device 114.”).
With respect to claim 8, Sugumaran in view of Shekar in view of Meyer teaches to identify a set of one or more attributes to be detected; and identify the monitoring location based, at least in part, on the identified set of one or more attributes to be detected (See at least Sugumaran FIG. 7-8 and Paragraph 64 “Based on the difference map, areas 282 and 284 are identified as needing touch-up. For example, it may be that the prescription was not followed precisely enough with respect to areas 282 and 284. In that case, the difference map (or some indication or metrics indicative of the difference map) can be provided to one or more machines 272-274 that can follow-up and spray additional chemicals on areas 282 and 284. In yet another example, rearward UAV 152, itself, has a chemical applicator can that can be used to treat spots 282 and 284 as well.” | Paragraphs 72-73 “Referring again to FIG. 7, the difference map can be output to generate a visually observable quality map. This is indicated by block 292. The quality map may include, for instance, a geographical representation of the field, and visually observable identifiers indicating the quality of the crop care operation, as it was performed on each of the identified locations in the field. In another example, only the areas where the operation was performed insufficiently are identified. The quality map can take a wide variety of other forms as well. Referring again to FIG. 7, the difference map can be used to perform other functions as well. For instance, it can be used to perform pattern identification 294 that may indicate problematic patterns. It can be used to perform error processing and error correction as indicated by block 296, and it can be used to identify machine problems and to generate correction indicators correcting those problems. Machine problems may include setup problems which indicate problems with respect to the configuration or setup of the machine, or they can indicate actual machine malfunctions. All of these are indicated by block 298.”).
With respect to claim 10, Sugumaran in view of Shekar in view of Meyer teach to obtain the sensor data indicative of the detected one or more attributes in the measurement area ahead of the agricultural work machine; identify the one or more attributes in the measurement area ahead of the agricultural work machine based on the sensor data indicative of the detected one or more attributes in the measurement area ahead of the agricultural work machine (See at least Sugumaran FIG. 4 and Paragraph 46 “UAV 152 thus first uses its one or more attribute sensors 112 to sense an attribute of an area of the worksite that is forward of the mobile crop care machine 102, as machine 102 is traveling in the forward direction. This is indicated by block 166 in FIG. 4. In doing so, UAV 104 can correlate the attribute signal with a position from which it is sensed, as indicated by positioning system 116.”).
With respect to claim 21, Sugumaran in view of Shekar in view of Meyer teach to further cause the one or more processors to control a controllable subsystem of the agricultural work machine based on the identified one or more attributes in the measurement area ahead of the agricultural work machine (See at least Sugumaran FIG. 4 and Paragraph 47) (See at least Meyer Paragraph 12 “In accordance with one embodiment, an unmanned aircraft with a sensor is assigned, in particular, to a self-propelled, attached or towed harvester, wherein said sensor monitors the plant population in front of the harvester and/or a transfer process of the harvested crop from the harvester to a transport vehicle in the harvesting mode. The sensor generates signals that are fed to a control unit in the harvesting mode, wherein said control unit controls an actuator based on the signals. The actuator influences at least one operating parameter of the transport vehicle (particularly its steering and/or driving speed) in order to automate the transfer process and/or of the harvester in order to automate the transfer process and/or to control another operating parameter of the harvester”)
With respect to claim 22, Sugumaran in view of Shekar in view of Meyer teach that the controllable subsystem comprises an actuator, a propulsion subsystem, or a steering subsystem (See at least Meyer Paragraph 12 “In accordance with one embodiment, an unmanned aircraft with a sensor is assigned, in particular, to a self-propelled, attached or towed harvester, wherein said sensor monitors the plant population in front of the harvester and/or a transfer process of the harvested crop from the harvester to a transport vehicle in the harvesting mode. The sensor generates signals that are fed to a control unit in the harvesting mode, wherein said control unit controls an actuator based on the signals. The actuator influences at least one operating parameter of the transport vehicle (particularly its steering and/or driving speed) in order to automate the transfer process and/or of the harvester in order to automate the transfer process and/or to control another operating parameter of the harvester.”).
With respect to claim 23, Sugumaran in view of Shekar in view of Meyer teach that the drone comprises one of an aerial vehicle or a ground-based vehicle (See at least Sugumaran FIG. 4 and Paragraph 46 “UAV 152 thus first uses its one or more attribute sensors 112 to sense an attribute of an area of the worksite that is forward of the mobile crop care machine 102, as machine 102 is traveling in the forward direction. This is indicated by block 166 in FIG. 4. In doing so, UAV 104 can correlate the attribute signal with a position from which it is sensed, as indicated by positioning system 116.”)
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Sugumaran (US 20170031365 A1) (“Sugumaran”) in view of Shekar (US 20210146977 A1) (“Shekar”) in view of Meyer (US 20120029732 A1) (“Meyer”) further in view of Lee (US 20210362742 A1) (“Lee”).
With respect to claim 7, Sugumaran in view of Shekar in view of Meyer fail to explicitly disclose to identify a performance of a sensor on-board the agricultural work machine; and generate the travel plan based, at least in part, on the identified performance of the sensor on-board the agricultural work machine.
Lee, however, teaches to identify a performance of a sensor on-board the agricultural work machine; and generate the travel plan based, at least in part, on the identified performance of the sensor on-board the agricultural work machine (See at least Lee Paragraphs 98-99 “The processor 170 may determine the possible autonomous traveling function of the ego vehicle, and may generate an autonomous traveling control signal based on the possible autonomous traveling function of the ego vehicle. The possible autonomous traveling function is determined based on at least one of the construction of the sensor mounted in the ego vehicle, the construction of an autonomous traveling algorithm, road environment, or weather environment, and the autonomous traveling function, such as LKA (Lane Keeping Assist), ACC (Adaptive Cruise Control), TJP (Traffic Jam Pilot), LCA (Lane Change Assist), and Exit/Merge, is determined. The construction of the sensor mounted in the ego vehicle may be determined through the kind of a sensor, such as a camera, a radar, a lidar, or a GPS, the position at which the sensor is mounted, and sensor performance, such as field of view (FOV), measurement distance, and sampling rate.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Sugumaran in view of Shekar in view of Meyer to include to identify a performance of a sensor on-board the agricultural work machine; and generate the travel plan based, at least in part, on the identified performance of the sensor on-board the agricultural work machine, as taught by Lee as disclosed above, in order to ensure accurate vehicle control (Lee Paragraph 5 “Therefore, there is a necessity for an improved system and device capable of providing a function upgraded from an existing autonomous traveling function or improved traveling performance by exchanging data through communication even without separately purchasing a higher-level autonomous vehicle or replacing the sensor with a high-performance sensor.”).
Claims 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Sugumaran (US 20170031365 A1) (“Sugumaran”) in view of Meyer (US 20120029732 A1) (“Meyer”).
With respect to claim 19, Sugumaran teaches an agricultural system comprising:
a sensor system disposed on a drone communicably coupled to and remotely positionable from an agricultural work machine at a worksite, the sensor system configured to detect one or more attributes2 in a measurement area ahead of the agricultural work machine, relative to a travel direction of the agricultural work machine, and generate sensor data indicative of the detected one or more attributes in the measurement area ahead of the agricultural work machine (See at least Sugumaran FIG. 4 and Paragraph 46 “UAV 152 thus first uses its one or more attribute sensors 112 to sense an attribute of an area of the worksite that is forward of the mobile crop care machine 102, as machine 102 is traveling in the forward direction. This is indicated by block 166 in FIG. 4. In doing so, UAV 104 can correlate the attribute signal with a position from which it is sensed, as indicated by positioning system 116.”);
one or more processors; and memory storing instructions, executable by the one or more processors, that, when executed by the one or more processors, cause the one or more processors to:
identify one or more of a performance of a sensor on-board the agricultural work machine, a latency of the agricultural work machine (See at least Sugumaran Paragraph 37), and a travel speed of the agricultural work machine (See at least Sugumaran Paragraph 15)
obtain the sensor data indicative of the detected one or more attributes in the measurement area ahead of the agricultural work machine; identify the one or more attributes in the measurement area ahead of the agricultural work machine based on the sensor data indicative of the detected one or more attributes in the measurement area ahead of the agricultural work machine (See at least Sugumaran FIG. 4 and Paragraph 46 “UAV 152 thus first uses its one or more attribute sensors 112 to sense an attribute of an area of the worksite that is forward of the mobile crop care machine 102, as machine 102 is traveling in the forward direction. This is indicated by block 166 in FIG. 4. In doing so, UAV 104 can correlate the attribute signal with a position from which it is sensed, as indicated by positioning system 116.”); and
generate a control signal based on the identified one or more attributes in the measurement area ahead of the agricultural work machine (See at least Sugumaran FIG. 4 and Paragraph 47 “UAV 104 then communicates an indication of the sensed attribute, and the location that it was sensed from, to mobile crop care machine 102 over link 108. This is indicated by block 168. Crop care controller 140 on machine 102 then processes the sensed attribute indicator to generate an action signal. This is indicated by block 170. For instance, when machine 102 is a sprayer, crop care controller 140 can generate a spraying prescription that prescribes one or more chemicals (such as the chemical type, the chemical concentration and its location of application).”).
Sugumaran fails to explicitly disclose to generate a travel plan for the drone based, at least, on the one or more of the performance of a sensor on-board the agricultural work machine, the latency of the agricultural work machine, and the travel speed of the agricultural work machine, the travel plan including a monitoring location defining a location to position the drone to have the sensor system, disposed on the drone, detect the one or more attributes in the measurement area ahead of the agricultural work machine; control travel of the drone based on the travel plan.
Meyer, however, teaches to generate a travel plan for the drone based, at least, on the one or more of the performance of a sensor on-board the agricultural work machine, the latency of the agricultural work machine, and the travel speed of the agricultural work machine, the travel plan including a monitoring location defining a location to position the drone to have the sensor system, disposed on the drone, detect the one or more attributes in the measurement area ahead of the agricultural work machine; control travel of the drone based on the travel plan (See at least Meyer Paragraph 16 “The signals of the sensor can also be used by the control unit for planning a route of the harvester. For this purpose, it is preferred that the aircraft initially flies over and maps the field from a sufficient height (i.e., a greater height than during harvesting) in order to prepare the route plan. This makes it possible to drive around immovable obstacles (such as larger rocks) or movable obstacles (e.g., animals) or areas of a field that are not suitable for harvesting, such as, e.g., waterholes with dense weed cover, or to stop the harvester in order to avoid a collision. The aircraft can also be used during the drive to the field in order to detect obstacles in advance and to drive around these obstacles (e.g., passages with insufficient height or width or severe roadway damage). In this case, only the aircraft may initially fly over and explore the planned driving route. Crop parameters determined by the sensor of the aircraft such as, for example, the plant size, the level of maturity, the moisture, the protein content, etc., can also be taken into account during the preparation of the route plan in order to collect largely homogenous (or well mixed) crop qualities in the individual load containers.” | Paragraphs 36-38 “During the harvesting process, the control unit 112 transmits data with respect to the current position of the harvester 10 to the flight control 170 via the interface 90, the receiving and transmitting device 92 and the transmitting and receiving unit 166. The flight control controls the aircraft 150 in such a way that it is always positioned at a constant height of a few meters above the harvester 10, namely slightly in front of the ejecting end of the discharging device 40 in the forward direction and between the harvester 10 and the transport vehicle 12 in the lateral direction … The harvester 10 is steered based on the signals of the sensor 156 that contain information on the position of the crop edge 54. They are merged with signals of the aforementioned sensor for determining the position of sensing bands 62 arranged at the divider point of the harvesting header 28, namely with consideration of the different measured positions of the crop edge 54 in the forward direction, and serve for controlling the steering device 114.”).
It would have been obvious to one of ordinary skill in the art to have modified the system of Sugumaran to include to generate a travel plan for the drone based, at least, on the one or more of the performance of a sensor on-board the agricultural work machine, the latency of the agricultural work machine, and the travel speed of the agricultural work machine, the travel plan including a monitoring location defining a location to position the drone to have the sensor system, disposed on the drone, detect the one or more attributes in the measurement area ahead of the agricultural work machine; control travel of the drone based on the travel plan, as taught by Meyer, in order ensure efficient preparation of the route for the agricultural work machine (Meyer Paragraph 8 “In one embodiment, a control unit is designed such that it controls an actuator for influencing an operating parameter of the harvester and/or the transport vehicle in real time based on signals of the sensor in the harvesting mode.”).
With respect to claim 20, Sugumaran in view of Meyer teaches to identify one or more of:
(i) one or more characteristics of an obstruction at a worksite, the one or more characteristics comprising one or more of a location of the obstruction or a future location of the obstruction (See at least Meyer Paragraph 16 “The signals of the sensor can also be used by the control unit for planning a route of the harvester. For this purpose, it is preferred that the aircraft initially flies over and maps the field from a sufficient height (i.e., a greater height than during harvesting) in order to prepare the route plan. This makes it possible to drive around immovable obstacles (such as larger rocks) or movable obstacles (e.g., animals) or areas of a field that are not suitable for harvesting, such as, e.g., waterholes with dense weed cover, or to stop the harvester in order to avoid a collision. The aircraft can also be used during the drive to the field in order to detect obstacles in advance and to drive around these obstacles (e.g., passages with insufficient height or width or severe roadway damage). In this case, only the aircraft may initially fly over and explore the planned driving route. Crop parameters determined by the sensor of the aircraft such as, for example, the plant size, the level of maturity, the moisture, the protein content, etc., can also be taken into account during the preparation of the route plan in order to collect largely homogenous (or well mixed) crop qualities in the individual load containers.”);
(ii) a set of one or more attributes to be detected; or
(iii) a performance of a sensor of the sensor system on the drone; and
generate the travel plan based on one or more of: (i) the one or more characteristics of an obstruction at a worksite (See at least Meyer Paragraph 16 “The signals of the sensor can also be used by the control unit for planning a route of the harvester. For this purpose, it is preferred that the aircraft initially flies over and maps the field from a sufficient height (i.e., a greater height than during harvesting) in order to prepare the route plan. This makes it possible to drive around immovable obstacles (such as larger rocks) or movable obstacles (e.g., animals) or areas of a field that are not suitable for harvesting, such as, e.g., waterholes with dense weed cover, or to stop the harvester in order to avoid a collision. The aircraft can also be used during the drive to the field in order to detect obstacles in advance and to drive around these obstacles (e.g., passages with insufficient height or width or severe roadway damage). In this case, only the aircraft may initially fly over and explore the planned driving route. Crop parameters determined by the sensor of the aircraft such as, for example, the plant size, the level of maturity, the moisture, the protein content, etc., can also be taken into account during the preparation of the route plan in order to collect largely homogenous (or well mixed) crop qualities in the individual load containers.”);
(ii) the set of one or more attributes to be detected; or
(iii) a performance of a sensor of the sensor system on the drone.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IBRAHIM ABDOALATIF ALSOMAIRY whose telephone number is (571)272-5653. The examiner can normally be reached M-F 7:30-5:30.
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/IBRAHIM ABDOALATIF ALSOMAIRY/Examiner, Art Unit 3667 /KENNETH J MALKOWSKI/Primary Examiner, Art Unit 3667
1 There is no limiting definition as to what constitutes an “attribute”, however the specification provides examples as to what may constitute an “attribute” in paragraphs 62-64
2 There is no limiting definition as to what constitutes an “attribute”, however the specification provides examples as to what may constitute an “attribute” in paragraphs 62-64
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