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 .
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.
Claim(s) 1 and 5-16 are rejected under 35 U.S.C. 103 as being unpatentable over She (US20180096602A1), and further in view of Gopalakri (US9524648B1) and Switkes (US20200160723A1).
Regarding claim 1, She teaches;
A multi-agent control system for controlling a plurality of agents to operate in a platoon (taught as communication between a first and second vehicle, and subsequent actions to allow the first vehicle to control the second, paragraph 0009, effectively creating a platoon/fleet), wherein each of the plurality of agents includes:
an actuator (taught as vehicles containing actuators, element 120, to control various vehicle subsystems, paragraph 0023);
a sensor unit including at least one sensor (taught as vehicles containing sensors, element 125);
a controller configured to control the actuator, the sensor unit, and each agent using an internal control signal (taught as each vehicle containing a computer, element 110, to operate the vehicle, paragraph 0013);
a first processor (taught as the computer detecting faults and failures of various components of the vehicle, paragraph 0022) configured to generate a malfunction signal by detecting a malfunction of the actuator, the sensor unit (taught as detecting sensor failure, paragraph 0022), or [interpreted to indicate that the detector only needs to be configured to detect any one of the elements between the actuator, the sensor, and the controller] the controller (taught as the computer detecting failures, including memory corruption [which is part of the computer controlling the vehicle], paragraph 0022); and
a switch (taught as a software function in the second vehicle computer, element 110, to broadcast a message regarding an event [events are failure/faults, paragraph 0025], paragraph 0026, to allow/apply control signals to actuate the second vehicle operations based on instructions from the first vehicle, paragraph 0042, when control is acknowledged between the first and second vehicle such that the first vehicle computer can help the second vehicle, paragraph 0047) configured to perform a switching operation based on the malfunction signal such that the controller uses a correction control signal received from at least one neighboring agent among the plurality of agents instead of the internal control signal (taught as, when receiving a notification of an event from/for a second vehicle, having the second vehicle apply a control signal from the first vehicle to actuate subsystems of the second vehicle, paragraph 0026), the multi-agent control system comprising:
a second processor configured to detect a malfunctioning agent among the plurality of agents based on the malfunction signal received from each of the plurality of agents (taught as the computer detecting events and signaling other vehicles in a communication network, paragraph 0025); and
a multi-agent controller configured to control the at least one neighboring agent to transmit the correction control signal to the malfunctioning agent such that the plurality of agents move in the platoon [[having a predetermined form]] (taught as, when receiving a notification of an event from/for a second vehicle, having the second vehicle apply a control signal from the first vehicle to actuate subsystems of the second vehicle, paragraph 0026, effectively letting the first vehicle to control the second),
wherein the correction control signal is generated based on a position estimation vector and a velocity estimation vector of the malfunctioning agent, which are calculated by the at least one neighboring agent (taught as the first vehicle calculating control instructions for the second vehicle, based on data received from the second vehicle, paragraph 0050).
While She does not specify a distinction between the controller and the multi-agent controller, such a configuration would be obvious to one of ordinary skill in the art, since it has been held that constructing a formerly integral structure in various elements involves only routine skill in the art. Nerwin v. Erlichman, 168 USPQ 177, 179. For example, one would think to assign different programs for the different functions within a CPU or ECU, or using multiple CPU/ECUs to promote redundancy.
However, She does not explicitly teach; plurality of agents move in the platoon having a predetermined form, such that the malfunctioning agent moves in the platoon while maintaining the predetermined form with other agents of the plurality of agents, by using the position estimation vector or the velocity estimation vector as a position vector or a velocity vector of the malfunctioning agent instead of the internal control signal of the malfunctioning agent.
Gopalakri teaches; such that the malfunctioning agent moves in the platoon [[while maintaining the predetermined form with other agents of the plurality of agents]] by using the position estimation vector or the velocity estimation vector as a position vector or a velocity vector of the malfunctioning agent instead of the internal control signal of the malfunctioning agent (taught as using parameter information to compare with other systems of another UAV, column 29 66-column 30 line 2, including speed and heading and location data of the first UAV, column 30 lines 13-15, with the second UAV (either received by or detected by the second UAV), column 30 lines 17-21, which is then compared to determine if the first UAV is compromised, column 30 lines 26-30).
first processor is configured to detect the malfunction of the sensor unit provided in an i-th agent V, based on differences between a position estimation vector and a velocity estimation vector v of a neighboring agent V,+ around the i-th agent V, which are calculated by the i-th agent V (taught as using parameter information to compare with other systems of another UAV, column 29 66-column 30 line 2, including speed and heading and location data of the first UAV, column 30 lines 13-15; the combination of information provided produces the equivalent of position and velocity vector data), among the plurality of agents, and a position data vector and a velocity data vector which are actually measured by the neighboring agent V,+, which are received from the neighboring agent V,+. (taught as comparing parameter data to determine if the first UAV is compromised, column 30 lines 26-30).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
However, Gopalakri does not explicitly teach;
such that the malfunctioning agent moves in the platoon while maintaining the predetermined form with other agents of the plurality of agents.
Switkes teaches; such that the malfunctioning agent moves in the platoon while maintaining the predetermined form with other agents of the plurality of agents (taught as, upon determining a malfunction [such as braking] with a vehicle, that a vehicle should stay maintain its position, paragraph 0051).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to maintain vehicle positions/formations in a platoon as taught by Switkes in order to maintain relative vehicle spacing. As taught by Switkes, one of the primary goals of platooning is typically to maintain a desired gap of platooning vehicles (paragraph 0031). To reiterate, one of ordinary skill in the art would recognize that forming a platoon would want to maintain a predetermined/desired gap between vehicles, as taught by Switkes, in a system designed to form/deal with a platoon taught by She and modified by Gopalakri [such that She, for example, would be maintaining a desired vehicle gap].
Regarding claim 5, She as modified by Gopalakri and Switkes teaches;
The multi-agent control system of Claim 3 (see claim 3 rejection). She further teaches; wherein the sensor unit includes a LiDAR sensor (taught as sensors including LIDAR, paragraph 0020) and a GPS sensor (taught as sensors including a GPS device, paragraph 0021). However, She does not explicitly teach; wherein the first processor is further configured to: calculate the position estimation vector si+1 of the neighboring agent Vi+1 based on a distance between the i-th agent Vi and the at least one neighboring agent Vi+1, which is measured by the LiDAR sensor of the i-th agent Vi, and a current position of the i-th agent Vi, which is measured by the GPS sensor of the i-th agent Vi, and calculate the velocity estimation vector Q of the neighboring agent Vi+i is calculated based on a vector obtained by differentiating the distance between the i-th agent Vi and the neighboring agent Vi+1, which is measured by the LiDAR sensor of the i-th agent Vi, and a current speed of the i-th agent Vi, which is measured by the i-th agent Vi,
Gopalakri teaches; the position estimation vector si+1 of the neighboring agent Vi+1 is calculated based on a distance between the i-th agent Vi and the at least one neighboring agent Vi+1, which is measured by the LiDAR sensor of the i-th agent Vi (taught as the UAVs using proximity sensors including lidar, radar, sonar and so forth, column 13 lines 13-15), and a current position of the i-th agent Vi, which is measured by the GPS sensor of the i-th agent Vi (taught as the UAVs using positioning sensors including GPS, column 7 lines 46-51), the velocity estimation vector Q of the neighboring agent Vi+i is calculated based on a vector obtained by differentiating the distance between the i-th agent Vi and the neighboring agent Vi+1, which is measured by the LiDAR sensor of the i-th agent Vi, and a current speed of the i-th agent Vi, which is measured by the i-th agent Vi (taught as using parameter information to compare with other systems of another UAV, column 29 66-column 30 line 2, including speed and heading and location data of the first UAV, column 30 lines 13-15, with the second UAV (either received by or detected by the second UAV), column 30 lines 17-21).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
Regarding claim 6, She as modified by Gopalakri and Switkes teaches;
The multi-agent control system of Claim 1 (see claim 1 rejection). However, She does not explicitly teach; wherein, when a difference between a virtual control signal value, which is calculated based on a value obtained by subtracting a disturbance compensation signal for compensating for a disturbance di of the i-th agent V from a reference control signal value of the i-th agent Vi, and the internal control signal value, exceeds a preset threshold value, the first processor determines that a malfunction has occurred in the controller, the reference control signal value being generated based on the position reference vector sri and the velocity reference vector vri to be referenced by the i-th agent Vi to operate in the platoon.
Gopalakri teaches; wherein, when a difference between a virtual control signal value, which is calculated based on a value obtained by subtracting a disturbance compensation signal for compensating for a disturbance di of the i-th agent V from a reference control signal value of the i-th agent Vi, and the internal control signal value, exceeds a preset threshold value (implied in that parameter information is transmitted back to the first UAV to determine if a system is compromised, Column 30 lines 31-36), the first processor determines that a malfunction has occurred in the controller, the reference control signal value being generated based on the position reference vector sri and the velocity reference vector vri to be referenced by the i-th agent Vi to operate in the platoon (taught as comparing parameter data to determine if the first UAV is compromised, column 30 lines 26-30).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
Regarding claim 7, She as modified by Gopalakri and Switkes teaches;
The multi-agent control system of Claim 1 (see claim 1 rejection). However, She does not explicitly teach; wherein the second processor is configured to collect information about a difference value of at least one sensor output between the i-th agent V and a front agent Vi, and a difference value of at least one sensor output between the i-th agent V and a rear agent Vi+1, and to detect the malfunctioning agent based on the collected information.
Gopalakri teaches; wherein the second processor is configured to collect information about a difference value of at least one sensor output between the i-th agent V and a front agent Vi, and a difference value of at least one sensor output between the i-th agent V and a rear agent Vi+1, and to detect the malfunctioning agent based on the collected information (taught as using parameter information to compare with other systems of another UAV, column 29 66-column 30 line 2, including speed and heading and location data of the first UAV, column 30 lines 13-15, with the second UAV (either received by or detected by the second UAV), column 30 lines 17-21, which is then compared to determine if the first UAV is compromised, column 30 lines 26-30).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
Regarding claim 8, She as modified by Gopalakri and Switkes teaches;
The multi-agent control system of Claim 7 (see claim 7 rejection). However, She does not explicitly teach; wherein the second processor is configured to detect a sensor in which a failure has occurred, among the at least one sensor of the malfunctioning agent.
Gopalakri teaches; wherein the second processor is configured to detect a sensor in which a failure has occurred, among the at least one sensor of the malfunctioning agent (taught as determining a sensor malfunction based on parameter comparison, column 27 lines 21-31, such as a specific sensor like a compass, column 30 lines 31-36).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
Regarding claim 9, She teaches;
A multi-agent control system (taught as communication between a first and second vehicle, and subsequent actions to allow the first vehicle to control the second, paragraph 0009, effectively creating a platoon/fleet), comprising:
a plurality of agents (taught as host and second vehicles, element 101); and
a multi-agent controller configured to communicate with the plurality of agents to control the plurality of agents (taught as each vehicle containing a computer, element 110, to operate the vehicle, paragraph 0013), wherein each of the plurality of agents includes a sensor unit (taught as vehicles containing sensors, element 125), a transceiver (taught as a wireless communication interface, element 115), and a processor (taught as each vehicle containing a computer, element 110, to operate the vehicle, paragraph 0013, which serves to detect failures, paragraph 0022),
when receiving the malfunction information from the processor, the multi-agent controller is configured to select at least one neighboring agent, which is capable of controlling the malfunctioning agent from which the malfunction information is transmitted among the plurality of agents (taught as the second vehicle computer, element 110, to broadcast a message regarding an event [events are failure/faults, paragraph 0025], paragraph 0026, to allow/apply control signals to actuate the second vehicle operations based on instructions from the first vehicle, paragraph 0042), and connect the selected at least one neighboring agent and the malfunctioning agent to establish the communication therebetween (taught as acknowledging control/communication between the first and second vehicle such that the first vehicle computer can help the second vehicle, paragraph 0047,
wherein the correction control signal is generated based on a position estimation vector and a velocity estimation vector of the malfunctioning agent, which are calculated by the at least one neighboring agent (taught as the first vehicle calculating control instructions for the second vehicle, based on data received from the second vehicle, paragraph 0050).
While She does not specify a distinction between the controller and the multi-agent controller, such a configuration would be obvious to one of ordinary skill in the art, since it has been held that constructing a formerly integral structure in various elements involves only routine skill in the art. Nerwin v. Erlichman, 168 USPQ 177, 179. For example, one would think to assign different programs for the different functions within a CPU or ECU, or using multiple CPU/ECUs to promote redundancy.
However, She does not explicitly teach; wherein the first processor is configured to transmit malfunction information of a malfunctioning agent to the multi-agent controller through the transceiver, the selected at least one neighboring agent is configured to transmit a state estimation vector of the malfunctioning agent to the malfunctioning agent to control the malfunctioning agent the selected at least one neighboring agent is configured to transmit a state estimation vector, which is generated based on a position estimation vector and a velocity estimation vector of the malfunctioning agent, of the malfunctioning agent to the malfunctioning agent such that the malfunctioning agent moves in a platoon having a predetermined form while maintaining the predetermined form with other agents of the plurality of agents by using the position estimation vector or the velocity estimation vector as a position vector or a velocity vector of the malfunctioning agent instead of an internal control signal of the malfunctioning agent.
Gopalakri teaches; wherein the processor is configured to transmit malfunction information of a malfunctioning agent to the multi-agent controller through the transceiver (taught as a separate compromise module, element 136 from computing devices, element 104, using networks to communicate between UAVs, shown in Fig 1), the selected at least one neighboring agent is configured to transmit a state estimation vector of the malfunctioning agent to the malfunctioning agent to control the malfunctioning agent (implied in that parameter information is transmitted back to the first UAV to determine if a system is compromised, Column 30 lines 31-36), such that the malfunctioning agent moves in a platoon [[having a predetermined form while maintaining the predetermined form with other agents of the plurality of agents]] by using the position estimation vector or the velocity estimation vector as a position vector or a velocity vector of the malfunctioning agent instead of an internal control signal of the malfunctioning agent (taught as using parameter information to compare with other systems of another UAV, column 29 66-column 30 line 2, including speed and heading and location data of the first UAV, column 30 lines 13-15, with the second UAV (either received by or detected by the second UAV), column 30 lines 17-21, which is then compared to determine if the first UAV is compromised, column 30 lines 26-30),
wherein the processor provided in an i-th agent V, is configured to detect the malfunction of the sensor unit provided in the i-th agent V, based on differences between a position estimation vector sand a velocity estimation vector vof a neighboring agent Vi+ around the i-th agent V, which are calculated by the i-th agent V(taught as using parameter information to compare with other systems of another UAV, column 29 66-column 30 line 2, including speed and heading and location data of the first UAV, column 30 lines 13-15; the combination of information provided produces the equivalent of position and velocity vector data), among the plurality of agents, and a position data vector and a velocity data vector which are actually measured by the neighboring agent Vi+1, which are received from the neighboring agent V,+1 (taught as comparing parameter data to determine if the first UAV is compromised, column 30 lines 26-30).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
However, Gopalakri does not explicitly teach; such that the malfunctioning agent moves in the platoon while maintaining the predetermined form with other agents of the plurality of agents.
Switkes teaches; such that the malfunctioning agent moves in the platoon while maintaining the predetermined form with other agents of the plurality of agents (taught as, upon determining a malfunction [such as braking] with a vehicle, that a vehicle should stay maintain its position, paragraph 0051).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to maintain vehicle positions/formations in a platoon as taught by Switkes in order to maintain relative vehicle spacing. As taught by Switkes, one of the primary goals of platooning is typically to maintain a desired gap of platooning vehicles (paragraph 0031). To reiterate, one of ordinary skill in the art would recognize that forming a platoon would want to maintain a predetermined/desired gap between vehicles, as taught by Switkes, in a system designed to form/deal with a platoon taught by She and modified by Gopalakri [such that She, for example, would be maintaining a desired vehicle gap].
Regarding claim 10, She as modified by Gopalakri and Switkes teaches;
The multi-agent control system of Claim 9 (see claim 9 rejection). However, She does not explicitly teach; wherein the multi-agent controller is configured to generate a command signal for allowing the selected at least one neighboring agent to transmit the state estimation vector of the malfunctioning agent to the malfunctioning agent, and configured to transmit the command signal to the selected at least one neighboring agent.
Gopalakri teaches; wherein the multi-agent controller is configured to generate a command signal for allowing the selected at least one neighboring agent to transmit the state estimation vector of the malfunctioning agent to the malfunctioning agent, and configured to transmit the command signal to the selected at least one neighboring agent (implied in that parameter information is transmitted back to the first UAV to determine if a system is compromised, Column 30 lines 31-36, wherein the uncompromised UAV controls the compromised UAV, column 29 lines 54-58).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
Regarding claim 11, She as modified by Gopalakri and Switkes teaches;
The multi-agent control system of Claim 9 (see claim 9 rejection). However, She does not explicitly teach; wherein the selected at least one neighboring agent is configured to observe a motion of the malfunctioning agent in real time to calculate the state estimation vector of the malfunctioning agent, and configured to transmit the state estimation vector of the malfunctioning agent to the malfunctioning agent.
Gopalakri teaches; wherein the selected at least one neighboring agent is configured to observe a motion of the malfunctioning agent in real time to calculate the state estimation vector of the malfunctioning agent (taught as using parameter information to compare with other systems of another UAV, column 29 66-column 30 line 2, including speed and heading and location data of the first UAV, column 30 lines 13-15, with the second UAV (either received by or detected by the second UAV), column 30 lines 17-21), and configured to transmit the state estimation vector of the malfunctioning agent to the malfunctioning agent (implied in that parameter information is transmitted back to the first UAV to determine if a system is compromised, Column 30 lines 31-36, wherein the uncompromised UAV controls the compromised UAV, column 29 lines 54-58).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
Regarding claim 12, She as modified by Gopalakri and Switkes teaches;
The multi-agent control system of Claim 11 (see claim 11 rejection). However, She does not explicitly teach; wherein the observing the motion of the malfunctioning agent in the real-time is performed by a sensor unit of the selected at least one neighboring agent.
Gopalakri teaches; wherein the observing the motion of the malfunctioning agent in the real-time is performed by a sensor unit of the selected at least one neighboring agent (taught as using parameter information to compare with other systems of another UAV, column 29 66-column 30 line 2, including speed and heading and location data of the first UAV, column 30 lines 13-15, with the second UAV (either received by or detected by the second UAV), column 30 lines 17-21).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
Regarding claim 13, She as modified by Gopalakri and Switkes teaches;
The multi-agent control system of Claim 9 (see claim 9 rejection),. However, She does not explicitly teach; wherein the malfunctioning agent is configured to operate using, as a correction control signal, the state estimation vector received from the at least one neighboring agent, instead of an internal control signal generated by the malfunctioning agent.
Gopalakri teaches; wherein the malfunctioning agent is configured to operate using, as a correction control signal, the state estimation vector received from the at least one neighboring agent, instead of an internal control signal generated by the malfunctioning agent (taught as performing a remedial action, such as adjusting sensor output/recalibrate the compromised UAV, column 31 line 65 – column 32 line 2).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
Regarding claim 14, it has been determined that no further limitations exist apart from those previously addressed in claim 1. Therefore, claim 14 is rejected under the same rationale as claim 1.
Regarding claim 15, She as modified by Gopalakri and Switkes teaches;
The operating method of Claim 14 (see claim 1 rejection). However, She does not explicitly teach; wherein detecting the malfunction of the sensor unit further includes: calculating the position estimation vector of the neighboring agent V,+ based on a distance between the i-th agent V, and the at least one neighboring agent Vi+1 which is measured by the LiDAR sensor of the i-th agent V and a current position of the i-th agent V, which is measured by the GPS sensor of the i-th agent V, and calculating the velocity estimation vector Q of the neighboring agent V,+ based on a vector obtained by differentiating the distance between the i-th agent V, and the neighboring agent Vi+1, which is measured by the LiDAR sensor of the i-th agent V, and a current speed of the i-th agent V, which is measured by the i-th agent V.
Gopalakri teaches; wherein detecting the malfunction of the sensor unit further includes: calculating the position estimation vector of the neighboring agent V,+ based on a distance between the i-th agent V, and the at least one neighboring agent Vi+1 (taught as using parameter information to compare with other systems of another UAV, column 29 66-column 30 line 2, including speed and heading and location data of the first UAV, column 30 lines 13-15; the combination of information provided produces the equivalent of position and velocity vector data), which is measured by the LiDAR sensor of the i-th agent V (taught as proximity sensors including Lidar, column 13 lines 13-15), and a current position of the i-th agent V, which is measured by the GPS sensor of the i-th agent V, (taught as a first navigation system including GPS, column 7 lines 37-50), and calculating the velocity estimation vector Q of the neighboring agent V,+ based on a vector obtained by differentiating the distance between the i-th agent V, and the neighboring agent Vi+1, which is measured by the LiDAR sensor of the i-th agent V, and a current speed of the i-th agent V, which is measured by the i-th agent V (taught as using parameter information to compare with other systems of another UAV, column 29 66-column 30 line 2, including speed and heading and location data of the first UAV, column 30 lines 13-15; the combination of information provided produces the equivalent of position and velocity vector data).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to collect and send data as taught by Gopalakri in the system taught by She in order to improve malfunction detection and correction. Such additional information allows for more versatility, such as by providing calibration/correction (column 31 line 65-column 32 line 2) as well as more direct control solutions to a compromised/malfunctioning vehicle (column 34 lines 2-4). To reiterate, one would think to more explicitly receive heading and velocity data, as taught in Gopalakri, in the system taught by She, in order to improve potential recourse actions, including more options such as recalibrating sensors or providing direct control of the malfunctioning vehicle to a nearby, separate vehicle.
Regarding claim 16, it has been determined that no further limitations exist apart from those previously addressed in claim 15. Therefore, claim 16 is rejected under the same rationale as claim 15.
Response to Arguments
Applicant argues on pages 8-11 of the remarks that the amended claim material is not explicitly taught in the provided prior art; specifically, the applicant argues that Gopalakri does not teach using the position estimation vector of the velocity estimation vector of the malfunctioning agent instead of the internal control signal of the malfunctioning agent.
The examiner notes that the active control of the malfunctioning vehicle is primarily accomplished through She; Gopalakri is relied on to enhance She with the improved information of vectors and malfunction identification. Gopalakri, as admitted by the applicant, teaches the comparison of parameters (location, altitude, speed) [which effectively is a vector] between a first and a malfunctioning UAV, and defines a trigger to determine a malfunctioning vehicle. She teaches, upon receiving a trigger, using a first vehicle to control a malfunctioning vehicle. Thus, in combination, the systems of She would use the calculations/estimations taught by Gopalakri in order to improve the trigger She already has to navigate the malfunctioning vehicle.
Should the applicant contest the combination of art further, the examiner requests providing examples as to how the claimed application would react differently in a situation when compared to the combination of references.
Applicant argues on pages 11-12 that the new claims are allowable at least based on their dependencies on allowable material.
In light of the above rejections and arguments, this argument is rendered moot. Furthermore, She and Gopalakri additionally address the use of Lidar and GPS within each of their systems for proximity and navigation, and thus apply directly to the new material.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
For assisting prognostics/malfunctions in vehicles; US20200211393A1, US20190287317, US20190079540
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/GABRIEL ANFINRUD/Examiner, Art Unit 3662
/JELANI A SMITH/Supervisory Patent Examiner, Art Unit 3662