DETAILED ACTION
This action is in reply to the amendments and arguments filed September 22nd, 2026. Claims 1, 5, 6, 8, and 9 are currently pending.
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.
Claims 1, 5, 6, 8, and 9 are rejected under 35 U.S.C. 103 as being unpatentable over previously cited of record Liu et al. (US Pub. No. 20200097006 A1), herein after Liu, in further view of previously cited of record Clayton et al. (US Pub. No. 20180143003 A1), herein after Clayton, in further view of previously cited of record Song et al. (US Pub. No. 20170347066 A1), herein after Song, and further in view of previously cited of record Kim; NamGyun (US Pub. No. 20200139963 A1), herein after Kim.
Regarding claim 1, Liu teaches [a]n azimuth angle acquisition apparatus for a self-propellable vehicle, comprising: a processor configured to (Liu: Para. 0024 and 0025, teaching a vehicle system that determines the pose of the vehicle which includes the position and orientation of the vehicle): acquire an external state and an internal state, wherein the external state is a motion state of the vehicle detected externally from the vehicle, by an external state detector… disposed externally of the vehicle, and the internal state is the motion state of the vehicle detected from inside the vehicle by a yaw rate sensor provided in the vehicle (Liu: Para. 0046 and 0047, teaching that the vehicle can receive navigation signals from various sources such as navigation beacons, aviation navigation facilities, cellular network base stations, etc. which are then used to determine the position of the vehicle; and Para. 0070, teaching that the pose of the vehicle can be acquired from IMU sensors; and Para. 0009, teaching that the sensors for calculating the pose of the vehicle can include an inertial measurement unit (IMU) sensor); calculate an external azimuth angle using the acquired external state and calculate an internal azimuth angle using the acquired internal state (Liu: Para. 0071, teaching that raw sensor data is collected to process for the sake of determining the position and orientation of the vehicle; and Para. 0072, teaching that the position and orientation can be calculated by processing data from multiple sources combined together); determine a vehicle azimuth angle using the calculated external azimuth angle and the calculated internal azimuth angle (Liu: Para. 0041, teaching that the pose calculated is used for navigational purposes; and Para. 0078, teaching that the pose is estimated by weighing the raw data from multiple sensors and processing the sensor data together) by changing a priority level of the external azimuth angle and a priority level of the internal azimuth angle (Liu: Para. 0062 and 0066, teaching that the pose of the vehicle can be dynamically calculated based on the state of the vehicle and its location by adjusting the weight given to each sensor based on how accurate it is; and Para. 0077 and 0078, teaching that if the pose of the vehicle that is calculated differs from the current pose of the vehicle, then an adverse event is detected and the weights used to calculate the pose are updated as part of the semantic information of the vehicle) according to the motion state of the vehicle and a state of the external state detector (Liu: Para. 0073, teaching that the adverse event can include a pose of the vehicle or an indication that a sensor has diminished performance), wherein the processor is further configured to self-propel the vehicle by transmitting the determined vehicle azimuth angle to a travel control device and to control, via the travel control device, at least one actuator of the vehicle based on the determined vehicle azimuth angle to self-propel the vehicle (Liu: Para. 0046, teaching that the data on the pose of the vehicle is utilized to determine the course of the vehicle and maneuver the vehicle accordingly).
Liu is silent to the external state detector being arranged on a route on which the vehicle self-propels and including at least one of a camera and a LiDAR; increase the priority level of the external azimuth angle when the motion state of the vehicle is in a stopped state; and increase the priority level of the internal azimuth angle when the motion state of the vehicle is in a turning state.
In a similar field, Clayton teaches an external state detector being arranged on a route on which the vehicle self-propels and including at least one of a camera and a LiDAR disposed externally of the vehicle (Clayton: Para. 0029, teaching that the position and orientation of a vehicle can be calculated from images acquired from stationary cameras exterior to the vehicle) for the benefit of improving estimation of a vehicle’s position and orientation in an environment.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the sensors used to collect data used for calculating the position and orientation from Liu to utilize cameras installed in the environment exterior to the vehicle, as taught by Clayton, for the benefit of improving estimation of a vehicle’s position and orientation in an environment.
Liu in view of Clayton are silent to increase the priority level of the external azimuth angle when the motion state of the vehicle is in a stopped state; and increase the priority level of the internal azimuth angle when the motion state of the vehicle is in a turning state.
In a similar field, Song teaches calculating the orientation of a vehicle when the motion state of the vehicle is in a stopped state (Song: Para. 0071, teaching that the orientation of a vehicle is calculated specifically on the basis that it is in a stopped state) for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the weights for the sensor data used to calculate the position and orientation of a vehicle from Liu in view of Clayton to also be affected by the vehicle being in a stopped state, as taught by Song, for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
Liu in view of Clayton in further view of Song are silent to increase the priority level of the internal azimuth angle when the motion state of the vehicle is in a turning state.
In a similar field, Kim teaches calculating the orientation of a vehicle when the motion state of the vehicle is in a turning state (Kim: Para. 0075, teaching that the orientation of a vehicle is calculated based on the vehicle being in a turning state) for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the weights for the sensor data used to calculate the position and orientation of a vehicle from Liu in view of Clayton in further view of Song to also be weighed by the vehicle being in a turning state, as taught by Kim, for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
Regarding claim 5, Liu, Clayton, Song, and Kim remain as applied as in claim 1, and Liu goes on to further teach [t]he azimuth angle acquisition apparatus according to claim 1, wherein the processor corrects the internal azimuth angle using the external azimuth angle when the motion state of the vehicle is in a straight-ahead state and a probability of the external state azimuth angle, the probability being calculated using the acquired external state and indicating a certainty of the external azimuth angle, is equal to or larger than a predetermined threshold value, and increases the priority level of the internal azimuth angle and determines the vehicle azimuth angle when the probability of the external azimuth angle is less than the predetermined threshold value (Liu: Para. 0095 and 0096, teaching that the system calculates whether a current estimated pose satisfies or exceeds a threshold for the various sensors and adjusting the weight of the data from the sensors accordingly).
Regarding claim 6, Liu Clayton, Song, and Kim remain as applied as in claim 1, and Clayton goes on to further teach [t]he azimuth angle acquisition apparatus according to claim 1, wherein the external state detector includes a camera, and wherein the processor calculates the external azimuth angle of the vehicle using an image captured by the camera (Clayton: Para. 0029, teaching that the position and orientation of a vehicle can be calculated from images acquired from stationary cameras exterior to the vehicle).
Regarding claim 8, Liu teaches [a]n azimuth angle acquisition system for a self-propellable vehicle, comprising (Liu: Para. 0024 and 0025, teaching a vehicle system that determines the pose of the vehicle which includes the position and orientation of the vehicle): an external state detector disposed externally of the vehicle to detect a motion state of the vehicle externally from the vehicle; an internal state detector mounted on the vehicle to detect the motion state of the vehicle from inside the vehicle, the internal state detector being a yaw rate sensor (Liu: Para. 0046 and 0047, teaching that the vehicle can receive navigation signals from various sources such as navigation beacons, aviation navigation facilities, cellular network base stations, etc. which are then used to determine the position of the vehicle; and Para. 0070, teaching that the pose of the vehicle can be acquired from IMU sensors; and Para. 0009, teaching that the sensors for calculating the pose of the vehicle can include an inertial measurement unit (IMU) sensor); an azimuth angle acquisition apparatus, the azimuth angle acquisition apparatus comprising: a processor configured to: calculate an external azimuth angle using an external state of the vehicle and an internal azimuth angle using an internal state of the vehicle, wherein the external state is the motion state of the vehicle detected by the external state detector, and the internal state is the motion state of the vehicle detected by the internal state detector (Liu: Para. 0071, teaching that raw sensor data is collected to process for the sake of determining the position and orientation of the vehicle; and Para. 0072, teaching that the position and orientation can be calculated by processing data from multiple sources combined together); determine a vehicle azimuth angle using the calculated external azimuth angle and the calculated internal azimuth angle, wherein the vehicle azimuth angle is used to self-propel the vehicle (Liu: Para. 0041, teaching that the pose calculated is used for navigational purposes; and Para. 0078, teaching that the pose is estimated by weighing the raw data from multiple sensors and processing the sensor data together) by changing a priority level of the external azimuth angle and a priority level of the internal azimuth angle (Liu: Para. 0062 and 0066, teaching that the pose of the vehicle can be dynamically calculated based on the state of the vehicle and its location by adjusting the weight given to each sensor based on how accurate it is; and Para. 0077 and 0078, teaching that if the pose of the vehicle that is calculated differs from the current pose of the vehicle, then an adverse event is detected and the weights used to calculate the pose are updated as part of the semantic information of the vehicle) according to the motion state of the vehicle and a state of the external state detector that detects the external state (Liu: Para. 0073, teaching that the adverse event can include a pose of the vehicle or an indication that a sensor has diminished performance); and a travel control device configured to receive the determined vehicle azimuth angle from the processor and control at least one actuator of the vehicle based on the determined vehicle azimuth angle to self-propel the vehicle (Liu: Para. 0046, teaching that the data on the pose of the vehicle is utilized to determine the course of the vehicle and maneuver the vehicle accordingly).
Liu is silent to the external state detector being arranged on a route on which the vehicle self-propels and including at least one of a camera and a LiDAR; increase the priority level of the external azimuth angle when the motion state of the vehicle is in a stopped state, and increase the priority level of the internal azimuth angle when the motion state of the vehicle is in a turning state.
In a similar field, Clayton teaches an external state detector being arranged on a route on which the vehicle self-propels and including at least one of a camera and a LiDAR disposed externally of the vehicle to detect a motion state of the vehicle externally from the vehicle (Clayton: Para. 0029, teaching that the position and orientation of a vehicle can be calculated from images acquired from stationary cameras exterior to the vehicle) for the benefit of improving estimation of a vehicle’s position and orientation in an environment.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the sensors used to collect data used for calculating the position and orientation from Liu to utilize cameras installed in the environment exterior to the vehicle, as taught by Clayton, for the benefit of improving estimation of a vehicle’s position and orientation in an environment.
Liu in view of Clayton are silent to increase the priority level of the external azimuth angle when the motion state of the vehicle is in a stopped state, and increase the priority level of the internal azimuth angle when the motion state of the vehicle is in a turning state.
In a similar field, Song teaches calculating the orientation of a vehicle when the motion state of the vehicle is in a stopped state (Song: Para. 0071, teaching that the orientation of a vehicle is calculated specifically on the basis that it is in a stopped state) for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the weights for the sensor data used to calculate the position and orientation of a vehicle from Liu in view of Clayton to also be affected by the vehicle being in a stopped state, as taught by Song, for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
Liu in view of Clayton in further view of Song are silent to increase the priority level of the internal azimuth angle when the motion state of the vehicle is in a turning state.
In a similar field, Kim teaches calculating the orientation of a vehicle when the motion state of the vehicle is in a turning state (Kim: Para. 0075, teaching that the orientation of a vehicle is calculated based on the vehicle being in a turning state) for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the weights for the sensor data used to calculate the position and orientation of a vehicle from Liu in view of Clayton in further view of Song to also be weighed by the vehicle being in a turning state, as taught by Kim, for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
Regarding claim 9, Liu teaches [a] method of acquiring an azimuth angle of a self-propellable vehicle, comprising (Liu: Para. 0024 and 0025, teaching a vehicle system that determines the pose of the vehicle which includes the position and orientation of the vehicle): acquiring an external state and an internal state, wherein the external state is a motion state of the vehicle detected externally from the vehicle by an external state detector… disposed externally of the vehicle, and the internal state is the motion state of the vehicle detected from inside of the vehicle by a yaw rate sensor provided in the vehicle (Liu: Para. 0046 and 0047, teaching that the vehicle can receive navigation signals from various sources such as navigation beacons, aviation navigation facilities, cellular network base stations, etc. which are then used to determine the position of the vehicle; and Para. 0070, teaching that the pose of the vehicle can be acquired from IMU sensors; and Para. 0009, teaching that the sensors for calculating the pose of the vehicle can include an inertial measurement unit (IMU) sensor); calculating an external azimuth angle using the acquired external state, and an internal azimuth angle using the acquired internal state (Liu: Para. 0071, teaching that raw sensor data is collected to process for the sake of determining the position and orientation of the vehicle; and Para. 0072, teaching that the position and orientation can be calculated by processing data from multiple sources combined together); and determining a vehicle azimuth angle using the calculated external azimuth angle and the internal azimuth angle (Liu: Para. 0041, teaching that the pose calculated is used for navigational purposes; and Para. 0078, teaching that the pose is estimated by weighing the raw data from multiple sensors and processing the sensor data together) by changing a priority level of the external azimuth angle and a priority level of the internal azimuth angle (Liu: Para. 0062 and 0066, teaching that the pose of the vehicle can be dynamically calculated based on the state of the vehicle and its location by adjusting the weight given to each sensor based on how accurate it is; and Para. 0077 and 0078, teaching that if the pose of the vehicle that is calculated differs from the current pose of the vehicle, then an adverse event is detected and the weights used to calculate the pose are updated as part of the semantic information of the vehicle) according to the motion state of the vehicle and a state of an external state detector that detects the external state (Liu: Para. 0073, teaching that the adverse event can include a pose of the vehicle or an indication that a sensor has diminished performance); and controlling at least one actuator of the vehicle based on the determined vehicle azimuth angle to self-propel the vehicle (Liu: Para. 0041, teaching that the pose calculated is used for navigational purposes; and Para. 0078, teaching that the pose is estimated by weighing the raw data from multiple sensors and processing the sensor data together).
Liu is silent to the external state detector being arranged on a route on which the vehicle self-propels and including at least one of a camera and a LiDAR disposed externally of the vehicle; increasing the priority level of the external azimuth angle when the motion state of the vehicle is in a stopped state; and increasing the priority level of the internal azimuth angle when the motion state of the vehicle is in a turning state.
In a similar field, Clayton teaches an external state detector including at least one of a camera and a LiDAR disposed externally of the vehicle (Clayton: Para. 0029, teaching that the position and orientation of a vehicle can be calculated from images acquired from stationary cameras exterior to the vehicle) for the benefit of improving estimation of a vehicle’s position and orientation in an environment.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the sensors used to collect data used for calculating the position and orientation from Liu to utilize cameras installed in the environment exterior to the vehicle, as taught by Clayton, for the benefit of improving estimation of a vehicle’s position and orientation in an environment.
Liu in view of Clayton are silent to increasing the priority level of the external azimuth angle when the motion state of the vehicle is in a stopped state; and increasing the priority level of the internal azimuth angle when the motion state of the vehicle is in a turning state.
In a similar field, Song teaches calculating the orientation of a vehicle when the motion state of the vehicle is in a stopped state (Song: Para. 0071, teaching that the orientation of a vehicle is calculated specifically on the basis that it is in a stopped state) for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the weights for the sensor data used to calculate the position and orientation of a vehicle from Liu in view of Clayton to also be affected by the vehicle being in a stopped state, as taught by Song, for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
Liu in view of Clayton in further view of Song are silent to increasing the priority level of the internal azimuth angle when the motion state of the vehicle is in a turning state.
In a similar field, Kim teaches calculating the orientation of a vehicle when the motion state of the vehicle is in a turning state (Kim: Para. 0075, teaching that the orientation of a vehicle is calculated based on the vehicle being in a turning state) for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the weights for the sensor data used to calculate the position and orientation of a vehicle from Liu in view of Clayton in further view of Song to also be weighed by the vehicle being in a turning state, as taught by Kim, for the benefit of improved awareness of a vehicle’s position and orientation in relation to other objects.
Response to Arguments
Applicant's arguments filed September 22nd, 2026 have been fully considered but they are not persuasive.
Applicant’s amendments, filed September 22nd, 2026, with respect to the rejections of claims 1, 5, and 6 under 101 have been fully considered and have rendered the 101 rejections of claims 1, 5, and 6 moot. Therefore, the 101 rejections of claims 1, 5, and 6 have been withdrawn.
Applicant’s amendments, filed September 22nd, 2026, with respect to the rejection of claim 5 under 112(b) has been fully considered and has rendered the 112(b) rejection of claim 5 moot. Therefore, the 112(b) rejection of claim 5 has been withdrawn.
Applicant’s arguments, see Remarks, filed May 27th, 2026, with respect to the 101 rejection of claim 8 have been fully considered and are persuasive. The 101 rejection of claim 8 has been withdrawn.
Applicant's arguments filed September 22nd, 2026 with respect to the 103 rejections of record have been fully considered but they are not persuasive.
Applicant contends (see page 7 line 17 through page 8 line 9, filed September 22nd, 2026) that Liu in view of Kim is deficient in teaching that the priority of the internal azimuth angle is increased when the motion state of the vehicle is in a turning state as the prior art of Liu does not contemplate adjusting the sensor weights in response to the vehicle being in a turning state and the prior art of Kim merely is aware if the vehicle is turning but is deficient in teaching adjusting the weight given to any sensors in response to the vehicle being in a turning state. The examiner respectfully disagrees. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). The examiner notes that paragraphs 0077 of Liu states “If the difference between a pose indicated by the processed measurement(s) from the pre-processor 404 and the current estimated pose is greater than a pre-determined threshold, the semantic information extractor 406 may record an adverse event for the related one or more associated sensor(s) 402” (emphasis added) which shows that the detection of adverse events is based on both the current pose of the vehicle and changes in the pose of the vehicle. The prior art of Liu even states in paragraph 0026 “In some embodiments, the robotic device 102 may be equipped with any of a number of additional sensors useful for SLAM and navigation, such as… an inertial measurement unit (IMU) or components thereof (e.g., accelerometer, gyroscope, magnetometer, etc.), an orientation sensor, and a monocular image sensor” (emphasis added) and one ordinarily skilled in the art would understand that a gyroscope being used as part of an inertial measurement unit but not as an orientation sensor is used to collect data regarding rates of change of the orientation of the vehicle which commonly occurs in a motion state of turning. The prior art of Kim is then brought in to teach adjusting the calculations of the pose of the vehicle based on whether the vehicle is turning and how large the turning radius and steering angle is (Kim: Para. 0075) which when combined with the prior art of Liu teaches a system that adjusts the weight given to an internal sensor for detecting the orientation (azimuth angle) based on whether the vehicle is actively turning.
Applicant contends (see page 9 line 11 through page 14, filed September 22nd, 2026) that Liu in view of Song is deficient in teaching that the priority of the external azimuth angle is increased when the motion state of the vehicle is in a stopped state as the adverse events of Liu of the vehicle being stuck or in a collision are not the same as the vehicle being stopped and even if they were applicable nothing in Liu discloses adjusting the weight of external sensors while the prior art of Song does not teach determining external azimuth angles, internal azimuth angles, or priority levels of the angels. The examiner respectfully disagrees. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). The examiner notes that, regarding the adjustment of weights of external sensors, Liu does teach in paragraph 0061 the use of GNSS receivers to obtain pose information and paragraph 0062 goes on to describe an adverse event of “a GNSS receiver may be unreliable indoors due to signal strength issues” which, in combination with paragraphs 0062 and 0066 which teaches that the pose of the vehicle can be dynamically calculated based on the state of the vehicle and its location by adjusting the weight given to each sensor based on how accurate it is, one ordinarily skilled in the art would recognize that the prior art of Liu does adjust the weights (priority levels) of the data taken from external sources as needed. Regarding the contention against Song, the examiner notes that Liu is being used to teach calculating the external azimuth angles based on the position of the vehicle and changes in the position of the vehicle and adjusting the weights given to each sensor accordingly while the prior art of Song is being used to teach that the orientation and position of the vehicle and its sensors are specifically calculated in relation to the vehicle being in a stopped state.
Applicant contends (see page 11 line 20 through page 12, filed September 22nd, 2026) that Liu and Clayton is deficient in teaching calculating an external azimuth angle from a camera or LIDAR sensor that is external to the vehicle. The examiner respectfully disagrees. The examiner notes that Liu teaches in at least paragraph 0061 that “The robotic device may also use a GNSS receiver to obtain global position information to supplement or facilitate acquisition of pose information” while paragraph 0047 states “The radio module 270 may be configured to receive navigation signals, such as signals from aviation navigation facilities, etc., and provide such signals to the processor 220 and/or the navigation unit 222 to assist in robotic device navigation”. As such, Liu is sufficient in teaching the use of a variety of external sources for information used to calculate the azimuth angle (orientation such as heading). The prior art of Clayton is brought in to teach that a camera disposed external to a vehicle and along its path of travel can also be one of the sources of information used to calculate the azimuth angle which can also have weights applied to the external sensor data based on detections of adverse events.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/A.K.M./Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663
