DETAILED ACTION
Status of Claims
This action is in reply to the arguments filed on 12 February 2026.
Claims 1, 7, 28 & 30 have been amended.
Claims 3-6, 13-27, & 32-35, 39 have been canceled.
Claims 1, 2, 7-12, 28-31 & 36-38 are currently pending and have been examined.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The Examiner respectfully rescinds the claim objection to claim 30 in view of the claimed amendments.
Applicant’s arguments, see pages 8-11, filed 12 February 2026, with respect to the rejection(s) of claim(s) 1, 30, 31 and 36 under 35 U.S.C. 103 and claim(s) 7-12, 37 and 38 under 35 U.S.C. 102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Morrison et al. US 2022/0039313 A1 and Ebrahimi Afrouzi et al. US 2022/0026920 A1.
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.
Morrison + Becke
Claims 1, 2, 7-12, 30-31 & 36-38 are rejected under 35 U.S.C. 103 as being unpatentable over Morrison et al. US 2022/0039313 A1 in view of Ebrahimi Afrouzi et al. US 2022/0026920, hereafter Afrouzi.
Claim 1
Regarding Claim 1, Morrison teaches An autonomous electric mower (see at least Morrison Abstract: An autonomous lawn mower is described) comprises: a computer (see at least Morrison P0022: improve the functioning of a computer through function optimization, improved processing efficiencies, improved and optimized autonomous behavior of mower(s), etc.); a Lidar sensor; a color camera; a depth sensing camera; a GPS sensor (see at least Morrison P0027: The exterior of the body 132 supports various sensors including but not limited to forward viewing camera (s) 120, rear viewing camera(s) 122, side viewing camera(s) 138, radar antenna 136, global navigation satellite system (GNSS) antenna 118, communications antennas 114 and 116 as well as a number of other sensors ( described in detail with respect to FIG. 2) that are within the body 132. Additional sensor elements may include one or more of cameras (whether stereo, RGB, monochromatic, infrared, ultraviolet, hyperspectral, etc.), radar( s ), lidar( s ), accelerometer(s ), gyroscope(s), torque sensor(s), magnetometer(s), location system(s), battery management systems, wheel encoder(s), motor sensor(s), orientation sensor(s), and/or the like); and at least one blade motor and blade coupled to the blade motor for cutting (see at least Morrison P0023: The mower has one or more drive mechanisms, e.g., motors, facilitating movement of the mower as well as rotating the cutting blades, where the drive mechanism is of a type commensurate with the energy source); and wherein the computer is operable to: determine the mower location based on at least one of the Lidar sensor, color camera, GPS, and depth sensing camera (see at least Morrison P0033: Mower pose (location and orientation) may be detected, received, or determined based at least in part on the one or more sensor systems described above); instruct the mower to move along a path according to a predetermined route plan; instruct the mower to cut according to a predetermined cutting pattern (see at least Morrison P0046: The mow pattern 322 may be associated with mow parameters 338 (e.g., mower speed, blade height, blade speed, deck type of side discharge, rear discharge, or mulching etc.) that are used while performing the mow pattern 322 and Fig. 10 showing the mow pattern generation occurs before the mow pattern execution, which the examiner interprets as a predetermined plan); monitor the path for obstacles as the mower is moving along the path and cutting based on data from the color camera, depth camera, and LIDAR sensor (see at least Morrison P0107: the sensors detect an unknown obstacle (i.e., not accounted for in the mow pattern) that may impede the progress of the mower, the mower controller executes an interrupt (for example, obstacle handling program 334 of FIG. 3) that handles the obstacle);
Morrison does not teach the following, however Afrouzi does teach:
at least one traction motor and drive wheel coupled to the traction motor (para. 0708: “the robot may include, but is not limited to include, one or more of a casing, a chassis including a set of wheels, a motor to drive the wheels…control motors such as wheel motors); and
instruct the […] to continue moving along the path and to continue cutting if data from at least one of the color camera, depth camera, and LIDAR sensor is unobstructed even if one of the color camera, depth sensing camera, and LIDAR sensor is obstructed (para. 0820: “In some embodiments, a sensor may become inoperable or damages and the processor may cease to receive usable data from the sensor. In such cases, the processor may use data collected by one or more other sensors of the robot to continue operations in a best effort manner until the sensor becomes operable..”).
Afrouzi teaches the robot may be wheeled (e.g., rigidly fixed, suspended fixed, steerable, suspended steerable, caster, or suspended caster), legged, or tank tracked. In some embodiments, the wheels, legs, tracks, etc. of the robot may be controlled individually or controlled in pairs (e.g., like cars) or in groups of other sizes, such as three or four as in omnidirectional wheels. Afrouzi does not disclose a lawn mower, however Morrison does. Because both Afrouzi & Morrison teach autonomous robots, it would have been obvious to one skilled in the art to substitute the cleaning robot of Afrouzi with the lawn mower of Morrison to achieve predictable results.
It would have been obvious to one of ordinary skill in the art before the effective filing date to [combine/modify] the method of Afrouzi with the lawn mower of Morrison to improve operation of the robot such that trajectory, path planning, and object detection is improved in situations where data becomes unavailable due to malfunctioning sensors (Afrouzi para. 0742). Therefore, the design incentives of improved operation provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Claim 2
Regarding Claim 2, Morrison & Afrouzi discloses the limitations as shown in the rejection of Claim 1 above. Morrison does not disclose the limitation of wherein the mower comprises a vehicle body, and the Lidar sensor is arranged to have a 360-degree view from the vehicle body. However, Afrouzi, in paragraph 0819 teaches “This may be applied to both depth readings and feature readings in scenarios wherein the FOV of the robot is limited to a particular angle around the 360 degrees perimeter of the robot and scenarios wherein the FOV of the robot encompasses 360 degrees through combination of the FOVs of complementary sensors positioned around the robot body or by a rotating LIDAR device.”.
Afrouzi teaches the robot may be wheeled (e.g., rigidly fixed, suspended fixed, steerable, suspended steerable, caster, or suspended caster), legged, or tank tracked. In some embodiments, the wheels, legs, tracks, etc. of the robot may be controlled individually or controlled in pairs (e.g., like cars) or in groups of other sizes, such as three or four as in omnidirectional wheels. Afrouzi does not disclose a lawn mower, however Morrison does. Because both Afrouzi & Morrison teach autonomous robots, it would have been obvious to one skilled in the art to substitute the cleaning robot of Afrouzi with the lawn mower of Morrison to achieve predictable results.
It would have been obvious to one of ordinary skill in the art before the effective filing date to [combine/modify] the method of Afrouzi with the lawn mower of Morrison to improve operation of the robot such that trajectory, path planning, and object detection is improved in situations where data becomes unavailable due to malfunctioning sensors (Afrouzi para. 0742). Therefore, the design incentives of improved operation provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Claim 7
Regarding Claim 7, Morrison teaches An autonomous electric mower (see at least Morrison Abstract: An autonomous lawn mower is described) for mowing a lawn comprising: a computer (see at least Morrison P0022: improve the functioning of a computer through function optimization, improved processing efficiencies, improved and optimized autonomous behavior of mower(s), etc.); a Lidar sensor; a plurality of depth sensing cameras; and a plurality of color cameras (see at least Morrison P0027: The exterior of the body 132 supports various sensors including but not limited to forward viewing camera (s) 120, rear viewing camera(s) 122, side viewing camera(s) 138, radar antenna 136, global navigation satellite system (GNSS) antenna 118, communications antennas 114 and 116 as well as a number of other sensors ( described in detail with respect to FIG. 2) that are within the body 132. Additional sensor elements may include one or more of cameras (whether stereo, RGB, monochromatic, infrared, ultraviolet, hyperspectral, etc.), radar( s ), lidar(s), accelerometer(s ), gyroscope(s), torque sensor(s), magnetometer(s), location system(s), battery management systems, wheel encoder(s), motor sensor(s), orientation sensor(s), and/or the like), wherein the computer is operable, based on the data generated from each of the Lidar sensor, depth sensing cameras, and color cameras, to: determine the location of the mower (see at least Morrison P0033: Mower pose (location and orientation) may be detected, received, or determined based at least in part on the one or more sensor systems described above); instruct the mower to move along a path; instruct the mower to cut; (see at least Morrison P0046: The mow pattern 322 may be associated with mow parameters 338 (e.g., mower speed, blade height, blade speed, deck type of side discharge, rear discharge, or mulching etc.) that are used while performing the mow pattern 322 and Fig. 10 showing the mow pattern generation occurs before the mow pattern execution; detect an obstacle; and instruct the mower to avoid the obstacle (see at least Morrison P0107: the sensors detect an unknown obstacle (i.e., not accounted for in the mow pattern) that may impede the progress of the mower, the mower controller executes an interrupt (for example, obstacle handling program 334 of FIG. 3) that handles the obstacle).
Morrison does not teach the following, however Afrouzi does teach:
instruct the […] to continue moving along the path and to continue cutting if data from at least one of the color camera, depth camera, and LIDAR sensor is unobstructed even if one of the color camera, depth sensing camera, and LIDAR sensor is obstructed (para. 0820: “In some embodiments, a sensor may become inoperable or damages and the processor may cease to receive usable data from the sensor. In such cases, the processor may use data collected by one or more other sensors of the robot to continue operations in a best effort manner until the sensor becomes operable..”).
Afrouzi teaches the robot may be wheeled (e.g., rigidly fixed, suspended fixed, steerable, suspended steerable, caster, or suspended caster), legged, or tank tracked. In some embodiments, the wheels, legs, tracks, etc. of the robot may be controlled individually or controlled in pairs (e.g., like cars) or in groups of other sizes, such as three or four as in omnidirectional wheels. Afrouzi does not disclose a lawn mower, however Morrison does. Because both Afrouzi & Morrison teach autonomous robots, it would have been obvious to one skilled in the art to substitute the cleaning robot of Afrouzi with the lawn mower of Morrison to achieve predictable results.
It would have been obvious to one of ordinary skill in the art before the effective filing date to [combine/modify] the method of Afrouzi with the lawn mower of Morrison to improve operation of the robot such that trajectory, path planning, and object detection is improved in situations where data becomes unavailable due to malfunctioning sensors (Afrouzi para. 0742). Therefore, the design incentives of improved operation provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Claim 8
Regarding Claim 8, Morrison teaches the limitations of claim 7 and the computer applies a first machine learning image-based sensor processing model to determine the location of the mower and a second machine learning image-based sensor processing model to detect the obstacle (see at least Morrison P0066: the objects may be specifically identified through object recognition algorithms to identify trees, bushes, buildings, etc. Such identification may be performed using machine learning algorithms… various neural networks may be trained to output object identification and location based on at least a portion of the sensor data the examiner interprets neural networks to output location as an example of the first machine learning model, and object identification as an example of the second machine learning model).
Claim 9
Regarding Claim 9, Morrison teaches the limitations of claim 8 and the computer is further operable to compare the data of a first sensor type to the data of a second sensor type to validate the location of the mower and presence of the obstacle (see at least Morrison P0051: During mowing, the mower may collect additional data regarding the property and use this additional data to update the mow pattern to, for example, add new obstacles, remove obstacles that are no longer present, update mower parameters, and/or the like the examiner interprets adding new obstacles and removing old obstacles as an example of validating the presence of an obstacle and P0033: Motion characteristics (e.g., velocity, acceleration direction, and/or the like) may be available from GNSS receiver 214 and the monitoring sensors 216 (e.g., inertial sensors, accelerometers, magnetometers, wheel rotation sensors, and/or the like) the examiner interprets a GNSS receiver as an example of a first sensor type and monitoring sensors as an example of a second sensor type for validating location of the mower).
Claim 10
Regarding Claim 10, Morrison & Afrouzi discloses the limitations as shown in the rejection of Claim 9 above. Morrison does not disclose the limitation of the computer is further operable to instruct the mower to continue mowing when one sensor is obstructed by use of data generated from at least one of the unobstructed sensors. However, Afrouzi, in paragraph 0820 teaches “In some embodiments, a sensor may become inoperable or damages and the processor may cease to receive usable data from the sensor. In such cases, the processor may use data collected by one or more other sensors of the robot to continue operations in a best effort manner until the sensor becomes operable..”.
Afrouzi teaches the robot may be wheeled (e.g., rigidly fixed, suspended fixed, steerable, suspended steerable, caster, or suspended caster), legged, or tank tracked. In some embodiments, the wheels, legs, tracks, etc. of the robot may be controlled individually or controlled in pairs (e.g., like cars) or in groups of other sizes, such as three or four as in omnidirectional wheels. Afrouzi does not disclose a lawn mower, however Morrison does. Because both Afrouzi & Morrison teach autonomous robots, it would have been obvious to one skilled in the art to substitute the cleaning robot of Afrouzi with the lawn mower of Morrison to achieve predictable results.
It would have been obvious to one of ordinary skill in the art before the effective filing date to [combine/modify] the method of Afrouzi with the lawn mower of Morrison to improve operation of the robot such that trajectory, path planning, and object detection is improved in situations where data becomes unavailable due to malfunctioning sensors (Afrouzi para. 0742). Therefore, the design incentives of improved operation provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Claim 11
Regarding Claim 11, Morrison teaches the limitations of claim 7 and at least one cutting blade defining a cutting plane, and at least one blade motor for rotating the cutting blade, and at least one cutting-plane lift motor for adjusting the height of the cutting blade relative to the ground (see at least Morrison P0046: The mow pattern 322 may be associated with mow parameters 338 (e.g., mower speed, blade height, blade speed, deck type of side discharge, rear discharge, or mulching etc.) that are used while performing the mow pattern 322 and P0042: The actuator drive interface 310 may support control of the actuators 210 of FIG. 2 (e.g., drive motors, brake system, blade motors, deck actuator, etc.)).
Claim 12
Regarding Claim 12, Morrison teaches the limitations of claim 11 and the computer is operable to monitor the power during mowing (see at least Morrison P0033: monitoring sensors 216 including, but not limited to,… battery management systems), and to adjust the power during mowing based on controlling the at least one blade motor, vehicle ground speed, and the cutting plane lift motor (see at least Morrison P0036: The motor controller circuits (power switching) 245 may be separate from the motors or built into the motors and P0024: The mower has one or more drive mechanisms, e.g., motors, facilitating movement of the mower as well as rotating the cutting blades, where the drive mechanism is of a type commensurate with the energy source).
Claim 30
Regarding Claim 30, Morrison teaches An autonomous electric mower system (see at least Morrison Abstract: An autonomous lawn mower is described) comprising: a perception module (see at least Morrison Fig. 3 sensor data 318), route planning module (see at least Morrison Fig. 3 pattern and map generator 328), localization module (see at least Morrison Fig. 3 sensor data 318 which the examiner notes includes a GNSS sensor depicted in Fig. 2, 218), blade cutting module (see at least Morrison Fig. 3 maw parameters 338), and navigation module (see at least Morrison Fig. 3 mow pattern following 332),
Further wherein a sensor module is operable to collect data generated from each of a Lidar sensor, depth sensing cameras, and a color camera and communication the data to a navigation module that is operable to: (see at least Morrison P0027: The exterior of the body 132 supports various sensors including but not limited to forward viewing camera (s) 120, rear viewing camera(s) 122, side viewing camera(s) 138, radar antenna 136, global navigation satellite system (GNSS) antenna 118, communications antennas 114 and 116 as well as a number of other sensors ( described in detail with respect to FIG. 2) that are within the body 132. Additional sensor elements may include one or more of cameras (whether stereo, RGB, monochromatic, infrared, ultraviolet, hyperspectral, etc.), radar( s ), lidar( s ), accelerometer(s ), gyroscope(s), torque sensor(s), magnetometer(s), location system(s), battery management systems, wheel encoder(s), motor sensor(s), orientation sensor(s), and/or the like);
Morrison does not teach the following, however Afrouzi does teach:
wherein the navigation module comprises a traction controller
(para. 0708: “the robot may include, but is not limited to include, one or more of a casing, a chassis including a set of wheels, a motor to drive the wheels…control motors such as wheel motors); and
instruct the […] to continue moving along the path and to continue cutting if data from at least one of the color camera, depth camera, and LIDAR sensor is unobstructed even if one of the color camera, depth sensing camera, and LIDAR sensor is obstructed (para. 0820: “In some embodiments, a sensor may become inoperable or damages and the processor may cease to receive usable data from the sensor. In such cases, the processor may use data collected by one or more other sensors of the robot to continue operations in a best effort manner until the sensor becomes operable..”).
Afrouzi teaches the robot may be wheeled (e.g., rigidly fixed, suspended fixed, steerable, suspended steerable, caster, or suspended caster), legged, or tank tracked. In some embodiments, the wheels, legs, tracks, etc. of the robot may be controlled individually or controlled in pairs (e.g., like cars) or in groups of other sizes, such as three or four as in omnidirectional wheels. Afrouzi does not disclose a lawn mower, however Morrison does. Because both Afrouzi & Morrison teach autonomous robots, it would have been obvious to one skilled in the art to substitute the cleaning robot of Afrouzi with the lawn mower of Morrison to achieve predictable results.
It would have been obvious to one of ordinary skill in the art before the effective filing date to [combine/modify] the method of Afrouzi with the lawn mower of Morrison to improve operation of the robot such that trajectory, path planning, and object detection is improved in situations where data becomes unavailable due to malfunctioning sensors (Afrouzi para. 0742). Therefore, the design incentives of improved operation provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Claim 31
Regarding Claim 31, the combination of Morrison and Becke teaches the limitations of claim 30 and Morrison further teaches the blade cutting module includes a height adjustment motor and dedicated controller for adjusting the height of the blade plane (see at least Morrison P0038: The deck assembly 106 may comprise at least one drive motor 246 for the blades 248, at least one deck actuator 250 for raising and lowering the deck (104 in FIG. 2)), and wherein the blade cutting module is operable to optimize mowing efficiency by adjusting the height of the blade plane during mowing (see at least Morrison P0097: The method 1200 optimizes the mow pattern and its parameters on a macro-level to minimize power consumption and P0078: the method 1000 sets the mow parameters (e.g., mower speed, blade speed, blade deck height, deck type of side discharge, rear discharge, or mulching etc.) to be used during the mowing session. These parameters may be changed during the mowing session either in accordance with the mow task, via operator adjustment, or by the mower as the mower analyses the environment in which it is mowing).
Claim 36
Regarding Claim 36, the combination of Morrison and Becke teaches the limitations of claim 1 and Morrison further teaches the computer is programmed and operable to compute a detour if an obstacle is detected in the path of mower (see at least Morrison P0099: the addition of way points to alter the mow pattern or to define a previously unknown obstacle that is to be avoided, the examiner interprets additional waypoints as an example of a detour).
Claim 37
Regarding Claim 37, Morrison teaches the limitations of claim 7 and the computer is programmed and operable to compute a global path for the mower to mow the lawn (see at least Morrison P0093: The mow pattern is established as a series of waypoints that the mower travels between as it mows).
Claim 38
Regarding Claim 38, Morrison teaches the limitations of claim 37 and the computer is programmed and operable to compute a local path if an obstacle is detected, and wherein the local path departs the global path, avoids the obstacle, and returns to the global path (see at least Morrison P0104: the mower may not have a preplanned path around the tree and be enabled to use its sensors to circumnavigate the tree (or other obstacle). The process continues from waypoint to waypoint until the entire lawn is mowed while avoiding the obstacles and staying within the boundary the examiner interprets the preplanned path as an example of the global path, and circumnavigation as an example of a local path, after which the mower returns to the preplanned waypoints).
Blanton + Afrouzi
Claims 28 and 29 are rejected under 35 U.S.C. 103 as being unpatentable over US 11,951,977 B1, hereinafter Blanton, in view of Afrouzi.
Regarding Claim 28, Blanton teaches An autonomous electric vehicle system (see at least Blanton Abstract: Disclosed are solutions for an autonomous vehicle) comprising a main robotic unit and slave attachment, wherein the main robotic unit comprises at least one traction motor and wheel, a plurality of sensors and cameras for localization, navigation and perception (see at least Blanton C16 Ln65: Tractor 710 may also include a main body that houses various electrical components and electronics such as batteries, drive motors, a battery- or power-management system, component controllers, sensors ( e.g., LID AR, RADAR, IMU, inertial navigation systems…), and an attachment hitch for power supply, data/communication, and mechanically connecting the vehicle to a slave attachment; (see at least Blanton C17 Ln10: the mowing deck 701 may be cantilevered from tractor 710 without supporting wheels. Power may be provided through electrical connections to motors on mowing deck 701 to drive the mower blades the examiner interprets the mowing deck 701 as an example of a slave attachment, see also at least Fig. 7).
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Blanton Fig. 7 showing the autonomous mower 700 with a tractor 710 and mowing deck 701 attached
Blanton does not explicitly teach the following however Afrouzi does teach:
wherein the navigation module comprises a traction controller
(para. 0708: “the robot may include, but is not limited to include, one or more of a casing, a chassis including a set of wheels, a motor to drive the wheels…control motors such as wheel motors); and
further wherein the plurality of sensors and cameras include a Lidar sensor, a plurality of depth sensing cameras, and a plurality of color camera that are operable to collect data and communication the data to a navigation module that is operable to (para. 0777: The robot may include a camera. The data collected by the camera may be bundled with data collected by one or more of an OTS, an encoder, an IMU, a gyroscope, etc. The robot may also include a 3D or 2D LIDAR for measuring distances to objects as the robot moves within the environment. For example, FIG. 39A illustrates an example of a robot 3900 whose processor associates data from any of odometry, gyroscope, OTS, IMU, TOF, etc. with LIDAR data. The LIDAR data may be used as ground truth, from which a calibration may be derived by a processor of the robot. After training and during runtime, the processor may compare camera data bundled with data from any of odometry, gyroscope, OTS, IMU, TOF, etc. and eventually convergence occurs. Para. 0852: “In some embodiments, the robot captures a video of the environment while navigating around the environment. This may be at a same time of constructing the map of the environment. In embodiments, the camera used to capture the video may be a different or a same camera as the one used for SLAM.”)
instruct the […] to continue moving along the path and to continue cutting if data from at least one of the color camera, depth camera, and LIDAR sensor is unobstructed even if one of the color camera, depth sensing camera, and LIDAR sensor is obstructed (para. 0820: “In some embodiments, a sensor may become inoperable or damages and the processor may cease to receive usable data from the sensor. In such cases, the processor may use data collected by one or more other sensors of the robot to continue operations in a best effort manner until the sensor becomes operable..”).
Afrouzi teaches the robot may be wheeled (e.g., rigidly fixed, suspended fixed, steerable, suspended steerable, caster, or suspended caster), legged, or tank tracked. In some embodiments, the wheels, legs, tracks, etc. of the robot may be controlled individually or controlled in pairs (e.g., like cars) or in groups of other sizes, such as three or four as in omnidirectional wheels. Afrouzi does not disclose a lawn mower, however Blanton does. Because both Afrouzi & Morrison teach autonomous robots, it would have been obvious to one skilled in the art to substitute the cleaning robot of Afrouzi with the lawn mower of Morrison to achieve predictable results.
It would have been obvious to one of ordinary skill in the art before the effective filing date to [combine/modify] the method of Afrouzi with the lawn mower of Blanton to improve operation of the robot such that trajectory, path planning, and object detection is improved in situations where data becomes unavailable due to malfunctioning sensors (Afrouzi para. 0742). Therefore, the design incentives of improved operation provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Claim 29
Regarding Claim 29, the combination of Blanton and Afrouzi teaches the limitations of claim 28 and Blanton further teaches the slave attachment is a mowing deck (see at least Blanton C16 Ln63: Autonomous mower 700 may include a mowing deck 701 and a tractor 710).
Conclusion
Related References
The related art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2020/0378088 A1 by Anderson teaches a tractor system that for predicting and reacting to obscurant conditions of sensors, managing and mitigating obscured sensors of the work vehicle to complete the work task.
US 9538702 B2 by Balutis teaches a path planning and execution mower reacting to boundaries and obstacles.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KITO R ROBINSON whose telephone number is (571)270-3921. The examiner can normally be reached M-F 8:00am-5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, James Trammell can be reached at (571) 272-6712. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KITO R ROBINSON/Supervisory Patent Examiner, Art Unit 3664
