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 the Claims
This action is in response to the Applicant’s filing on August 12, 2026. Claims 1-19 are pending and examined below.
Response to Arguments
The previous rejections of claims 1-19 under 35 U.S.C. 103 are withdrawn in consideration of amended independent claims 1 and 11. However, new rejections of claims 1-5, 7-15, and 17-19 under 35 U.S.C. 103 are set forth below.
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 1-2 and 10-12 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. US 2022/0041163 by Lynn et al. (herein after “Lynn”), in view of U.S. Patent Application Publication No. US 2024/0149868 by Packer et al. (herein after “Packer”).
Note: Text written in bold typeface is claim language from the instant application. Text written in normal typeface are comments made by the Examiner and/or passages from the prior art reference(s).
Regarding claim 1, Lynn discloses a method of operating a robot, configured to follow, in a standard trajectory of the robot, a trajectory of a leader (Lynn ¶ [0066]: in pair mode, an etiquette-based vehicle is configured to follow, with hysteresis dynamics, a trajectory of a user), in a manner to avoid an obstacle, the obstacle having a trajectory that intersects with the standard trajectory of the robot (Lynn ¶ [0069]: an obstacle avoidance tuck (to avoid the pedestrian in position 21); Lynn ¶ [0113]: the vehicle can use sensors to determine whether obstacles are in the known path. In such embodiments, the vehicle can stop and wait for the obstacles to clear, send an alarm, and find pathways around the obstacles), the method comprising:
using a set of sensors of the robot to detect the obstacle (Lynn ¶ [0009]: a set of sensors; Lynn ¶ [0057]: A “sensor” in an etiquette-based vehicle is a device configured to provide optical, radio, or other information about a set of objects in the environment of the vehicle, wherein the information is provided as a set of electrical signals for processing by a controller to manage movement of the vehicle; Lynn ¶ [0113]: the vehicle can use sensors to determine whether obstacles are in the known path);
using data from the set of sensors to determine, by a controller of the robot coupled to the set of sensors (Lynn ¶ [0104]: a smart-follow module fitted with a set of sensors and a controller configured to manage movement of an autonomous host self-powered vehicle), a set of parameters characterizing motion of the obstacle relative to the robot based on the standard trajectory of the robot in order to follow the leader (Lynn ¶ [0069]: The tuck behavior during the transition period can be represented by a cubic spline curve based on the following parameters: distance and angle between the vehicle and the user; velocity of the user; velocity of the obstacle; distance from the vehicle to the obstacle; Lynn ¶ [0113]: the vehicle can use sensors to determine whether obstacles are in the known path);
after implementation of the obstacle avoidance protocol, causing, by the controller, the robot to return to following the trajectory of the leader (Lynn ¶ [0070]: The vehicle is configured to return to heel following position under appropriate circumstances).
It is noted that Lynn discloses detecting objects in the environment of a vehicle but fails to particularly disclose under a condition wherein the obstacle is outside of the standard trajectory of the robot:
evaluating, by the controller, a risk of a collision between the obstacle and the robot based on the standard trajectory of the robot and the trajectory of the obstacle, the risk of the collision being a risk that the robot will come within a non-zero threshold distance of the obstacle; and
under a circumstance wherein the evaluated risk exceeds a predetermined threshold, causing, by the controller, implementation of an obstacle avoidance protocol to cause the robot to avoid the obstacle by at least the non-zero threshold distance.
However, Packer, in the same field of endeavor, teaches under a condition wherein the obstacle is outside of the standard trajectory of the robot (Packer ¶ [0068]: the perception component 522 may include functionality to perform object detection, segmentation, and/or classification. In some examples, the perception component 522 may provide processed sensor data that indicates a presence of an agent (e.g., entity) that is proximate to the vehicle 502; Examiner interprets Packer to teach a system and method that detects all agents proximate to a vehicle including agents outside of the vehicle’s current trajectory):
using a set of sensors of the robot to detect the obstacle (Packer ¶ [0016]: The vehicle computing system may be configured to identify agents in the environment. In some examples, the agents may be identified based on sensor data from sensors (e.g., cameras, motion detectors, light detection and ranging (LIDAR), radio detection and ranging (RADAR), etc.) of the vehicle);
using data from the set of sensors to determine, by a controller of the robot coupled to the set of sensors (Packer: vehicle computing device 504 in Fig. 5), a set of parameters characterizing motion of the obstacle relative to the robot based on the standard trajectory of the robot in order to follow the leader (Packer ¶ [0080]: the collision avoidance component 530 may include an agent trajectory component 534. The agent trajectory component 534 may be configured to determine one or more possible trajectories associated with an agent in an environment in which the vehicle 502 is operating. In some examples, the trajectories may include any number of possible paths in which the agent 114 may travel from a current position (e.g., at the time of perception) and/or based on a direction of travel; Packer: agent trajectories 106(1), 106(2) and 106(3) in Fig. 1);
evaluating, by the controller, a risk of a collision between the obstacle and the robot based on the standard trajectory of the robot and the trajectory of the obstacle (Packer ¶ [0041]: based on a determination of the bounds (e.g., agent enter point 212, agent exit point 214, vehicle enter point 208, vehicle exit point 210) of one or more potential collision zones 202 between the vehicle 102(1) and the agent 114(1), the vehicle computing system may apply a time-space overlap to each potential collision zone 202 to determine a risk of collision in the potential collision zone 202), the risk of the collision being a risk that the robot will come within a non-zero threshold distance of the obstacle (Packer ¶ [0035]: the vehicle computing system may determine that a potential collision zone 120, such as collision zone 120(3), may exist between the vehicle 102(1) and the agent 114 based on a trajectory 106, such as trajectory 106(2), being within a threshold distance (e.g., 2 meters, 3 meters, 3 feet, 5 feet, etc.) of the path polygon 104. In some examples, the threshold distance may be based on a pre-defined distance. In various examples, the threshold distance may be determined based on a known or perceived width of the agent 114(1). In some examples, the threshold distance may be determined based on a known or perceived width of the agent 114(1) plus an agent buffer. The agent buffer may represent a safety buffer around the agent 114);
under a circumstance wherein the evaluated risk exceeds a predetermined threshold, causing, by the controller, implementation of an obstacle avoidance protocol to cause the robot to avoid the obstacle by at least the non-zero threshold distance (Packer ¶ [0050]: In the illustrative example of FIG. 3A, the vehicle computing device may determine, on the time-space overlap 300, that an overlap 332 between the vehicle 302 and the agent 306 exists in the potential collision zone 304. Based on the overlap 332, the vehicle computing device may determine that a risk of collision in the potential collision zone is high and that the vehicle computing device should cause the vehicle to perform an action to avoid collision; Packer ¶ [0051]: FIG. 3B is an illustration of a time-space overlap 300 in which the collision avoidance system may determine a low risk of collision between the vehicle 302 and the agent 306 based on an agent position cone 308 not overlapping with a vehicle position cone 310 along the planned path; Packer ¶ [0043]: A high risk (e.g., probability) of collision may include a probability of collision above a first threshold (e.g., 25%, 30%, 40%, etc.). A low risk of collision may include a probability of collision below a second threshold (e.g., 5%, 7%, 10%, etc.)).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and method that allow a following vehicle to avoid obstacles of Lynn to include the collision prediction, risk assessment and object avoidance of Packer with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to detect and avoid objects in an operating environment of a vehicle (Packer ¶ [0002]).
Regarding claim 2, the combination of Lynn and Packer discloses wherein the obstacle avoidance protocol includes causing the robot to have a lateral offset from the standard trajectory (Lynn ¶ [0069]: While performing obstacle avoidance, the paired vehicle executes a tuck behavior—a transition defined by a cubic spline curve. Specifically, when the vehicle encounters an obstacle, such as pedestrian 21, it tucks behind the user 22, transitioning to a 0° angle, measured from the centerline of the user 22 at point 221; Lynn: heel-following positions 13A-C and tuck positions 23A-C in Fig. 2).
Regarding claim 10, the combination of Lynn and Packer discloses wherein the robot performs the method autonomously (Lynn ¶ [0066]: Since the user and the vehicle are both self-powered and constitute a dynamic combination of components, the vehicle's controller is programmed to cause the vehicle to behave, i.e., to move, in accordance with these principles, in a range of distinct dynamic contexts; Lynn ¶ [0104]: a smart-follow module fitted with a set of sensors and a controller configured to manage movement of an autonomous host self-powered vehicle).
Regarding claim 11, Lynn discloses a robot configured to follow, in a standard trajectory of the robot, a trajectory of a leader (Lynn ¶ [0066]: in pair mode, an etiquette-based vehicle is configured to follow, with hysteresis dynamics, a trajectory of a user) in a manner to avoid an obstacle (Lynn ¶ [0069]: an obstacle avoidance tuck (to avoid the pedestrian in position 21); Lynn ¶ [0113]: the vehicle can use sensors to determine whether obstacles are in the known path. In such embodiments, the vehicle can stop and wait for the obstacles to clear, send an alarm, and find pathways around the obstacles), the robot comprising:
a body (Lynn: etiquette-based vehicle in Figs. 1-2, 5-9 and 12-20) including a set of sensors (Lynn ¶ [0009]: a set of sensors; Lynn ¶ [0057]: A “sensor” in an etiquette-based vehicle is a device configured to provide optical, radio, or other information about a set of objects in the environment of the vehicle, wherein the information is provided as a set of electrical signals for processing by a controller to manage movement of the vehicle; Lynn ¶ [0113]: the vehicle can use sensors to determine whether obstacles are in the known path) and a drive mechanism (Lynn ¶ [0008]: a mechanical drive system to cause movement of such vehicle);
a controller disposed in the body and coupled to the set of sensors and the drive mechanism (Lynn ¶ [0010]: a controller, coupled to the mechanical drive system, to manage movement of such vehicle; Lynn ¶ [0104]: a smart-follow module fitted with a set of sensors and a controller configured to manage movement of an autonomous host self-powered vehicle);
wherein the controller is configured to:
detect the obstacle using the set of sensors (Lynn ¶ [0009]: a set of sensors; Lynn ¶ [0057]: A “sensor” in an etiquette-based vehicle is a device configured to provide optical, radio, or other information about a set of objects in the environment of the vehicle, wherein the information is provided as a set of electrical signals for processing by a controller to manage movement of the vehicle; Lynn ¶ [0113]: the vehicle can use sensors to determine whether obstacles are in the known path);
determine, using data from the set of sensors, a set of parameters characterizing motion of the obstacle relative to the robot based on the standard trajectory of the robot in order to follow the leader (Lynn ¶ [0069]: The tuck behavior during the transition period can be represented by a cubic spline curve based on the following parameters: distance and angle between the vehicle and the user; velocity of the user; velocity of the obstacle; distance from the vehicle to the obstacle; Lynn ¶ [0113]: the vehicle can use sensors to determine whether obstacles are in the known path);
cause, after implementation of the obstacle avoidance protocol, the robot to return to following the trajectory of the leader (Lynn ¶ [0070]: The vehicle is configured to return to heel following position under appropriate circumstances).
It is noted that Lynn discloses detecting objects in the environment of a vehicle but fails to particularly disclose determine a trajectory of the obstacle with the obstacle outside the standard trajectory of the robot;
evaluate a risk of a collision between the obstacle and the robot based on the standard trajectory of the robot and the trajectory of the obstacle, the risk of the collision being a risk that the robot will come within a non-zero threshold distance of the obstacle;
cause, under a circumstance wherein the evaluated risk exceeds a predetermined threshold, implementation of an obstacle avoidance protocol to cause the robot to avoid the obstacle by at least the non-zero threshold distance.
However, Packer, in the same field of endeavor, teaches detect the obstacle using the set of sensors (Packer ¶ [0016]: The vehicle computing system may be configured to identify agents in the environment. In some examples, the agents may be identified based on sensor data from sensors (e.g., cameras, motion detectors, light detection and ranging (LIDAR), radio detection and ranging (RADAR), etc.) of the vehicle);
determine a trajectory of the obstacle with the obstacle outside the standard trajectory of the robot (Packer ¶ [0017]: The vehicle computing system may determine one or more trajectories of the agent (e.g., positions, velocities, accelerations, etc. of the agent as it moves through an environment) based on the sensor data. The one or more trajectories of the agent may represent possible paths that a center of the agent may travel through the environment. The center of the agent may include an estimated center of mass, an estimated volumetric center point of the agent, or the like. Based on the path polygon of the vehicle and the one or more trajectories, the vehicle computing system may determine whether a potential collision zone exists between the vehicle and the agent; Examiner interprets Packer to teach a system and method that determines one or more trajectories for all agents proximate to a vehicle including agents outside of the vehicle’s current trajectory);
determine, using data from the set of sensors, a set of parameters characterizing motion of the obstacle relative to the robot based on the standard trajectory of the robot in order to follow the leader (Packer ¶ [0080]: the collision avoidance component 530 may include an agent trajectory component 534. The agent trajectory component 534 may be configured to determine one or more possible trajectories associated with an agent in an environment in which the vehicle 502 is operating. In some examples, the trajectories may include any number of possible paths in which the agent 114 may travel from a current position (e.g., at the time of perception) and/or based on a direction of travel; Packer: agent trajectories 106(1), 106(2) and 106(3) in Fig. 1);
evaluate a risk of a collision between the obstacle and the robot based on the standard trajectory of the robot and the trajectory of the obstacle (Packer ¶ [0041]: based on a determination of the bounds (e.g., agent enter point 212, agent exit point 214, vehicle enter point 208, vehicle exit point 210) of one or more potential collision zones 202 between the vehicle 102(1) and the agent 114(1), the vehicle computing system may apply a time-space overlap to each potential collision zone 202 to determine a risk of collision in the potential collision zone 202), the risk of the collision being a risk that the robot will come within a non-zero threshold distance of the obstacle (Packer ¶ [0035]: the vehicle computing system may determine that a potential collision zone 120, such as collision zone 120(3), may exist between the vehicle 102(1) and the agent 114 based on a trajectory 106, such as trajectory 106(2), being within a threshold distance (e.g., 2 meters, 3 meters, 3 feet, 5 feet, etc.) of the path polygon 104. In some examples, the threshold distance may be based on a pre-defined distance. In various examples, the threshold distance may be determined based on a known or perceived width of the agent 114(1). In some examples, the threshold distance may be determined based on a known or perceived width of the agent 114(1) plus an agent buffer. The agent buffer may represent a safety buffer around the agent 114);
cause, under a circumstance wherein the evaluated risk exceeds a predetermined threshold, implementation of an obstacle avoidance protocol to cause the robot to avoid the obstacle by at least the non-zero threshold distance (Packer ¶ [0050]: In the illustrative example of FIG. 3A, the vehicle computing device may determine, on the time-space overlap 300, that an overlap 332 between the vehicle 302 and the agent 306 exists in the potential collision zone 304. Based on the overlap 332, the vehicle computing device may determine that a risk of collision in the potential collision zone is high and that the vehicle computing device should cause the vehicle to perform an action to avoid collision; Packer ¶ [0051]: FIG. 3B is an illustration of a time-space overlap 300 in which the collision avoidance system may determine a low risk of collision between the vehicle 302 and the agent 306 based on an agent position cone 308 not overlapping with a vehicle position cone 310 along the planned path; Packer ¶ [0043]: A high risk (e.g., probability) of collision may include a probability of collision above a first threshold (e.g., 25%, 30%, 40%, etc.). A low risk of collision may include a probability of collision below a second threshold (e.g., 5%, 7%, 10%, etc.)).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and method that allow a following vehicle to avoid obstacles of Lynn to include the collision prediction, risk assessment and object avoidance of Packer with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to detect and avoid objects in an operating environment of a vehicle (Packer ¶ [0002]).
Claim 12 recites analogous limitations to claim 2 above and is therefore rejected on the same premise.
Claims 3 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. US 2022/0041163 by Lynn et al. (herein after “Lynn”), in view of U.S. Patent Application Publication No. US 2024/0149868 by Packer et al. (herein after “Packer”), further in view of U.S. Patent Application Publication No. US 2022/0281598 by Pescaru et al. (herein after “Pescaru”).
Note: Text written in bold typeface is claim language from the instant application. Text written in normal typeface are comments made by the Examiner and/or passages from the prior art reference(s).
Regarding claim 3, the combination of Lynn and Packer discloses avoiding an object by adjusting a lateral position of a vehicle left or right (Packer ¶ [0050]) but fails to particularly disclose wherein the obstacle avoidance protocol is selected from the group consisting of a cross and a duck.
However, Pescaru, in the same field of endeavor, teaches wherein the obstacle avoidance protocol is selected from the group consisting of a cross and a duck (Pescaru ¶ [0103]: At step 824, it is ascertained whether the ARD 702 has enough time to overtake the corresponding object on the left-hand side to avoid collision. In the event the ARD 702 has enough time to overtake the corresponding object on the left-hand side to avoid collision, at step 826, the trajectory of the ARD 702 is modified to enable it to overtake the object on the left-hand side; and step 818 is performed; Pescaru ¶ [0104]: In the event the ARD 702 does not have enough time to overtake the corresponding object on the left-hand side, at step 828, it is ascertained whether the ARD 702 has enough time to overtake the corresponding object on the right-hand side to avoid collision. In the event the ARD 702 has enough time to overtake the corresponding object on the right-hand side to avoid collision, at step 830, the trajectory of the ARD 702 is modified to enable it to overtake the object on the right-hand side, and step 818 is performed). Examiner interprets the left or right overtaking of Pescaru to be analogous to a cross or duck maneuver as defined in the specification of the instant application (¶ [0047]-[0048]). Depending on the trajectories of the robot and obstacle, overtaking an obstacle on the left or right can be interpreted as a cross or duck.
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and method that allow a following vehicle to avoid obstacles of Lynn modified by the collision prediction, risk assessment and object avoidance of Packer to further include the risk assessment and thresholds for determining when to begin obstacle avoidance that entails overtaking an obstacle on the left or right of Pescaru with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to enable a robotic device to avoid moving obstacles in its path as it moved from a first location to a second location (Pescaru ¶ [0003]).
Claim 13 recites analogous limitations to claim 3 above and is therefore rejected on the same premise.
Claims 4-5, 7-8, 14-15, and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. US 2022/0041163 by Lynn et al. (herein after “Lynn”), in view of U.S. Patent Application Publication No. US 2024/0149868 by Packer et al. (herein after “Packer”), further in view of U.S. Patent Application Publication No. US 2015/0153735 by Clarke et al. (herein after “Clarke”).
Note: Text written in bold typeface is claim language from the instant application. Text written in normal typeface are comments made by the Examiner and/or passages from the prior art reference(s).
Regarding claim 4, the combination of Lynn and Packer discloses determining a risk of collision between an obstacle and a vehicle based on comparing a space-time overlap but the combination of Lynn and Packer fails to explicitly disclose wherein evaluating risk of a collision includes evaluating a collision time and wherein the predetermined threshold is a value of the collision time.
However, Clarke, in the same field of endeavor, teaches wherein evaluating risk of a collision includes evaluating a collision time and wherein the predetermined threshold is a value of the collision time (Clarke ¶ [0308]: System 100 may provide driver assist functionality that monitors the vicinity around vehicle 200 and responds to the presence of another vehicle encroaching upon vehicle 200. Monitoring the vicinity around vehicle 200 may include monitoring a collision threshold. For example a collision threshold may include a time to collision or a minimum predetermined distance between vehicle 200 and other traffic. System 100 may further cause vehicle 200 to take evasive action to avoid encroaching traffic. For example, evasive action may include braking, changing lanes, or otherwise altering the course of vehicle 200; Clarke ¶ [0316]: A collision threshold based on a time to collision may be set to allow enough time for system 100 to effectively conduct evasive action to avoid collision).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and method that allow a following vehicle to avoid obstacles of Lynn modified by the collision prediction, risk assessment and object avoidance of Packer to further include the comparison of a time to collision to a collision threshold as a condition for initiating an evasive action of Clarke with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to allow an autonomous vehicle enough time to effectively conduct an evasive action to avoid collision (Clarke ¶ [0316]).
Regarding claim 5, the combination of Lynn, Packer and Clarke discloses wherein implementation of the obstacle avoidance protocol is deemed completed based on the collision time being above a return threshold (Clarke ¶ [0308]: System 100 may provide driver assist functionality that monitors the vicinity around vehicle 200 and responds to the presence of another vehicle encroaching upon vehicle 200. Monitoring the vicinity around vehicle 200 may include monitoring a collision threshold. For example a collision threshold may include a time to collision or a minimum predetermined distance between vehicle 200 and other traffic. System 100 may further cause vehicle 200 to take evasive action to avoid encroaching traffic. For example, evasive action may include braking, changing lanes, or otherwise altering the course of vehicle 200; Clarke ¶ [0316]: A collision threshold based on a time to collision may be set to allow enough time for system 100 to effectively conduct evasive action to avoid collision).
Examiner interprets Lynn to disclose a system and method for returning a following robot to a standard trajectory under appropriate circumstances. Packer teaches determining a risk of collision between an obstacle and a vehicle based on comparing a space-time overlap and generating a lateral position adjustment including a new path for a vehicle to avoid the obstacle. Clarke teaches initiating an evasive action to avoid a collision based on comparing a time to collision to a collision threshold. The combination of Lynn, Packer and Clarke teaches a system and method that will control a robot to follow a trajectory of a user and initiate an evasive action when a time to collision with a detected obstacle exceeds a collision threshold. When the time to collision does not exceed the collision threshold an evasive action is not performed and the robot will return to following a trajectory of the user.
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and method that allow a following vehicle to avoid obstacles of Lynn modified by the collision prediction, risk assessment and object avoidance of Packer and the comparison of a time to collision to a collision threshold as a condition for initiating an evasive action of Clarke to explicitly include not performing an evasive action when a time to collision is greater than a collision threshold of Clarke with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to allow an autonomous vehicle enough time to effectively conduct an evasive action to avoid collision (Clarke ¶ [0316]).
Regarding claim 7, Lynn discloses further comprising:
evaluating, by the controller, (i) a (Lynn ¶ [0069]: The tuck behavior during the transition period can be represented by a cubic spline curve based on the following parameters: distance and angle between the vehicle and the user; velocity of the user; velocity of the obstacle; distance from the vehicle to the obstacle; Lynn ¶ [0113]: the vehicle can use sensors to determine whether obstacles are in the known path); and
calculating an obstacle navigation decision factor based on the (Lynn ¶ [0113]: the vehicle can use sensors to determine whether obstacles are in the known path. In such embodiments, the vehicle can stop and wait for the obstacles to clear, send an alarm, and find pathways around the obstacles).
Examiner interprets the system and method of Lynn to determine or decide whether an obstacle is in a known path and find a path around an obstacle that is in the known path or to continue on the known path if an obstacle is not in the known path based on a velocity of an obstacle and a distance from a user.
It is noted Lynn fails to explicitly disclose further comprising: evaluating, by the controller, (i) a convergence speed of the obstacle and the robot.
However, Clarke, in the same field of endeavor, teaches further comprising: evaluating, by the controller, (i) a convergence speed of the obstacle and the robot (Clarke ¶ [0158]: processing unit 110 may construct a set of measurements for the detected objects. Such measurements may include, for example, position, velocity, and acceleration values (relative to vehicle 200) associated with the detected objects).
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and method that allow a following vehicle to avoid obstacles of Lynn modified by the collision prediction, risk assessment and object avoidance of Packer to explicitly include the determination of a relative velocity or convergence speed of a detected object and a vehicle of Clarke with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to enable a robotic device to allow an autonomous vehicle enough time to effectively conduct an evasive action to avoid collision (Clarke ¶ [0316]).
Regarding claim 8, Lynn discloses deciding whether an obstacle is in a known path and finding a pathway around an obstacle that is in a known path or continuing on a current path if an obstacle is not in a known path based on a velocity of an obstacle and a distance from a user but fails to particularly disclose wherein the obstacle navigation decision factor is compared to a decision threshold to determine a type of obstacle avoidance protocol to be implemented by the robot.
However, Packer, in the same field of endeavor, teaches wherein the obstacle navigation decision factor is compared to a decision threshold to determine a type of obstacle avoidance protocol to be implemented by the robot (Packer ¶ [0097]: the action component 540 may, based on a determination of risk (e.g., high, medium, or low risk), determine an action to take. The action may include slowing the vehicle to yield to the agent, stopping the vehicle to yield to the agent, changing lanes left, or changing lanes right. Based on the determined action, the vehicle computing device 504, such as through the system controller(s) 526, may cause the vehicle to perform the action. In at least some examples, such an action may be based on the probability of collision, as described in detail above; Packer ¶ [0043]: A high risk (e.g., probability) of collision may include a probability of collision above a first threshold (e.g., 25%, 30%, 40%, etc.). A low risk of collision may include a probability of collision below a second threshold (e.g., 5%, 7%, 10%, etc.). A medium risk of collision may include a probability of collision between the first and second thresholds). Examiner interprets Packer to teach determining an action to take based on a determination of risk as high, medium, or low which is determined by comparing a risk or probability of collision to a threshold.
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and method that allow a following vehicle to avoid obstacles of Lynn modified by the collision prediction, risk assessment and object avoidance of Packer to explicitly include the determination of a relative velocity or convergence speed of a detected object and a vehicle of Clarke to explicitly include determining an action to take to avoid an obstacle based on a comparison of a risk of collision to a threshold of Packer with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to detect and avoid objects in an operating environment of a vehicle (Packer ¶ [0002]).
Claim 14 recites analogous limitations to claim 4 above and is therefore rejected on the same premise.
Claim 15 recites analogous limitations to claim 5 above and is therefore rejected on the same premise.
Claim 17 recites analogous limitations to claim 7 above and is therefore rejected on the same premise.
Claim 18 recites analogous limitations to claim 8 above and is therefore rejected on the same premise.
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. US 2022/0041163 by Lynn et al. (herein after “Lynn”), in view of U.S. Patent Application Publication No. US 2024/0149868 by Packer et al. (herein after “Packer”) and U.S. Patent Application Publication No. US 2015/0153735 by Clarke et al. (herein after “Clarke”), further in view of U.S. Patent Application Publication No. US 2022/0281598 by Pescaru et al. (herein after “Pescaru”).
Note: Text written in bold typeface is claim language from the instant application. Text written in normal typeface are comments made by the Examiner and/or passages from the prior art reference(s).
Regarding claim 9, Lynn fails to particularly disclose wherein the type of obstacle avoidance protocol is selected from the group consisting of a cross and a duck.
However, Pescaru, in the same field of endeavor, teaches wherein the type of obstacle avoidance protocol is selected from the group consisting of a cross and a duck (Pescaru ¶ [0103]: At step 824, it is ascertained whether the ARD 702 has enough time to overtake the corresponding object on the left-hand side to avoid collision. In the event the ARD 702 has enough time to overtake the corresponding object on the left-hand side to avoid collision, at step 826, the trajectory of the ARD 702 is modified to enable it to overtake the object on the left-hand side; and step 818 is performed; Pescaru ¶ [0104]: In the event the ARD 702 does not have enough time to overtake the corresponding object on the left-hand side, at step 828, it is ascertained whether the ARD 702 has enough time to overtake the corresponding object on the right-hand side to avoid collision. In the event the ARD 702 has enough time to overtake the corresponding object on the right-hand side to avoid collision, at step 830, the trajectory of the ARD 702 is modified to enable it to overtake the object on the right-hand side, and step 818 is performed). Examiner interprets the left or right overtaking of Pescaru to be analogous to a cross or duck maneuver as defined in the specification of the instant application (¶ [0047]-[0048]). Depending on the trajectories of the robot and obstacle, overtaking an obstacle on the left or right can be interpreted as a cross or duck.
Therefore, given the teachings as a whole, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and method that allow a following vehicle to avoid obstacles of Lynn modified by the collision prediction, risk assessment and object avoidance including determining an action to take to avoid an obstacle based on a comparison of a risk of collision to a threshold of Packer and the determination of a relative velocity or convergence speed of a detected object and a vehicle of Clarke to further include the obstacle avoidance that entails overtaking an obstacle on the left or right of Pescaru with a reasonable expectation of success. A person of ordinary skill in the art would be motivated to make this modification in order to enable a robotic device to avoid moving obstacles in its path as it moved from a first location to a second location (Pescaru ¶ [0003]).
Claim 19 recites analogous limitations to claim 9 above and is therefore rejected on the same premise.
Allowable Subject Matter
Claims 6 and 16 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to the applicant’s disclosure:
US 2023/0356391 discloses a robot that determines a path around a detected obstacle by moving left or right (¶ [0072]).
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/N.P.L./Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666
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