DETAILED ACTION
Status of Claims
This Office action is in response to the amendment filed on 07/14/2026. Claims 1-20 are currently pending and are presented for examination.
Response to Amendment/Arguments
The amendment filed 07/14/2026 has been entered and applicant’s arguments filed 07/14/2026 have been fully considered.
Regarding claim objections:
Applicant has argued that the objections to claims 7 and 14 have been overcome by the filed amendment. The examiner agrees and has withdrawn the objections accordingly.
Regarding claim rejections under 35 U.S.C. § 101:
Applicant has argued that the claim rejections under 35 U.S.C. § 101 have been overcome by the filed amendment. The examiner agrees and has withdrawn these rejections accordingly.
Regarding claim rejections under 35 U.S.C. §§ 102 and 103:
Applicant’s arguments regarding the claim rejections under 35 U.S.C. §§ 102 and 103 are moot in view of the new grounds of rejection which are necessitated by the filed amendment.
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 1-4 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Tomida et al. (US 2025/0306202 A1), hereinafter referred to as Tomida, in view of Kean et al. (US 2022/0333344 A1), hereinafter referred to as Kean, and further in view of Wei et al. (the non-patent article “LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System”), hereinafter referred to as Wei.
Regarding claim 1:
Tomida discloses the following limitations:
“A machine comprising: … a perception sensor system that includes a plurality of sensors.” (Tomida ¶¶ 32-33: “sonar apparatus 100 is an apparatus that transmits an ultrasonic signal, receives an ultrasonic signal reflected by a target object (object), and performs detection of the target or the like. … Each sonar apparatus 100 includes one sensor 120, but may include a plurality of sensors 120.” Further, Tomida ¶ 44: “In a case where processing apparatus 320 is controller 110, peripheral monitoring sensor 310 is sensor 120. In a case where processing apparatus 320 is ECU 230, peripheral monitoring sensor 310 is sonar apparatus 100.”)
“and a controller configured to: identify a previously determined distance to a target.” (Tomida ¶ 8: “A vehicle according to an embodiment of the present disclosure includes a processing apparatus according to an embodiment of the present disclosure includes: a processor; and a memory having instructions that, when executed by the processor, cause the processor to perform operations comprising: inputting a distance measurement value and a past distance measurement value are input, the distance measurement value indicating a distance to a target object measured by a sensor at a first time point, the past distance measurement value indicating a distance to the target object measured by the sensor at one or more time points earlier than the first time point.”)
“obtain perception information from the perception sensor system, wherein the perception information includes respective perception data captured by the plurality of sensors.” (Tomida ¶¶ 33-34: “Sonar apparatus 100 includes controller 110 and sensor 120. Each sonar apparatus 100 includes one sensor 120, but may include a plurality of sensors 120. Controller 110 includes transmission/reception controller 111 and detector 112. Controller 110 outputs the detection result of the target object to a vehicle control apparatus (Electronic Control Unit: ECU).”)
“determine, based on at least one of the previously determined distance to the target, the position of the implement and the linkage, or the steering angle of the machine, validity information associated with the perception information; select, based on the validity information, a portion of the perception information that includes perception data … indicated by the validity information as valid, and that excludes perception data … indicated by the validity information as not valid; determine, based on the portion of the perception information, a current distance to the target.” (Tomida ¶ 76: “In a case where the value |dt−dt-1|/dw calculated based on the difference between distance measurement value dt and distance measurement value dt-1 is larger than the threshold, filter processor 322 determines that the distance measurement skipping has occurred. In FIG. 14, a large difference (value of Z01) between the current distance measurement value (time t5) and the one previous distance measurement value (time t4) indicates that the distance measurement value has largely changed, and therefore, it can be determined from FIG. 13 that distance measurement skipping has occurred.” Also, Tomida ¶ 70: “The distance measurement skipping indicates a state in which a distance measurement value that is temporarily significantly different is detected, and the target switching indicates that the target has been switched from a reflected wave from target A to a reflected wave from target B, for example.” This at least teaches to determine validity information based on “the previously determined distance to the target” as claimed. Note that the range of values below the threshold read on the “portion of the perception information.”)
“and cause, based on the current distance to the target, an automatic control operation associated with at least one of movement of the machine or movement of the implement and the linkage relative to the target.” (Tomida ¶ 7 discloses “determining whether the distance measurement value is valid or invalid based on the distance measurement value, the past distance measurement value, and movement information of the sensor; and outputting a control signal for controlling a controller of a vehicle on which the sensor is mounted based on a result of the determination.” Also, Tomida ¶ 51: “Collision determinator 330 determines whether the host vehicle will collide with the target based on the generated coordinates. In a case where collision determinator 330 determines that there is a possibility of the vehicle colliding with the target, collision determinator 330 performs control to avoid the collision by outputting it to a brake or a vehicle steering section (not illustrated) to operating an emergency brake or operate a steering wheel.” This at least teaches to cause an automatic control operation associated with “movement of the machine” as claimed.)
Note that under the broadest reasonable interpretation (BRI) of claim 1, consistent with the instant specification, the recited steps to “determine, based on at least one of the previously determined distance to the target, the position of the implement and the linkage, or the steering angle of the machine, validity information associated with the perception information” and to “cause, based on the current distance to the target, an automatic control operation associated with at least one of movement of the machine or movement of the implement and the linkage relative to the target” are each treated as an alternative limitation. Applicant has elected to use the phrase “at least one” in the claim language, and therefore, the BRI covers the scenario in which only one of each limitation applies. Therefore, while only the “the previously determined distance to the target” and the “movement of the machine” have been addressed here, the claim is still rejected in its entirety.
The following limitations are not specifically disclosed by Tomida, but are taught by Kean:
the machine comprising “an implement and a linkage.” (Kean ¶ 40 and FIG. 1 shown below disclose “a representative self-propelled work vehicle 100 in the form of, for example, a loader having a front-mounted work attachment 120 for modifying the proximate terrain.” Further, Kean ¶ 69 discloses that the work vehicle can include a “linkage.”)
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“wherein the plurality of sensors includes at least two different types of sensors.” (Kean ¶ 52: “Other sensors (not shown) may collectively define an obstacle detection system, alone or in combination with one or more aforementioned sensors for improved data collection, various examples of which may include ultrasonic sensors, laser scanners, radar wave transmitters and receivers, thermal sensors, imaging devices, structured light sensors, other optical sensors, and the like.”)
“a machine sensor system that includes a plurality of other sensors.” (Kean ¶¶ 49-50: “An exemplary work vehicle motion sensing system 204 may include inertial measurement units (IMUs) mounted to respective components of the work attachment 120 and/or boom assembly 102 and/or main frame 132, sensors coupled to piston-cylinder units to detect the relative hydraulically actuated extensions thereof, or any known alternatives as may be known to those of skill in the art. In various embodiments, additional sensors may be provided to detect machine operating conditions or positioning, including for example an orientation sensor, global positioning system (GPS) sensors, vehicle speed sensors, vehicle implement positioning sensors, and the like.”)
“obtain machine information from the machine sensor system; determine, based on the machine information, a position of the implement and the linkage and a steering angle of the machine.” (Kean ¶ 67 discloses, “upon triggering an automated loading feature, generating signals (step 340) for controlling at least an approach of the work vehicle 100 and attachment 120 to the loading area 10, in association with a desired discharge of material 16. This may for example include calculating and implementing a trajectory for the drivetrain 342 beginning at the current work vehicle position and speed and ending in an appropriate position corresponding to the loading area with zero ground speed, using a visual measurement of the location and orientation of the loading area 10 relative to the work vehicle 100 to generate and implement a steering trajectory 344 and dynamically adjust a steering angle of the work vehicle to follow the trajectory as the work vehicle approaches the loading area, and further calculating and implementing a trajectory for one or more attachments (e.g., via the boom cylinder) 346 beginning at the current height and ending at a loading height substantially synchronized with the arrival of the work vehicle relative to the loading area, and/or applying closed loop controls to ensure the boom and drivetrain follow the calculated trajectories.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the system of Tomida by allowing the system to work with a work vehicle such as a wheel loader as taught by Kean, as this is a simple substitution of one known element (i.e., the wheel loader of Kean) for another (i.e., the passenger vehicle of Tomida) to obtain predictable results (see MPEP 2143(I)(B)). A person having ordinary skill in the art could have replaced the passenger vehicle of Tomida with the wheel loader of Kean to achieve the predictable result of providing a wheel loader that can consider the positioning of its linkage and implement to determine the validity of distance measurements to target objects such as a truck or hopper to allow for efficient loading of materials.
The combination of Tomida and Kean does not specifically teach to consider the validity of the perception information “captured by the at least two different types of sensors” and to determine the current distance to the target “as a representative fused distance to the target based on distances associated with the perception data captured by the at least two different types of sensors.” However, Wei does teach these limitations. (Wei p. 5 last two paragraphs: “In this system, we first obtain images from the camera, then through the camera object detection system, we estimate the bounding box coordinates of beacons together with the confidence scores for each bounding box. Next, the detection bounding box from the single camera is mapped through a neural network (NN) into a distance and angle estimate, in order to be able to fuse that information with the distance and angle estimates of the LiDAR processing. On the other side, we have point cloud information from the LiDAR, then through LiDAR data processing, we estimate the distance and angle information of the detected beacons by the LiDAR. Through the LiDAR processing, we also obtain a pseudo-confidence score. With the LiDAR detection results in the form of distance and angle from both the camera and LiDAR, we fuse them together to obtain a final distance, angle and confidence score for each detection.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the system that is disclosed by the combination of Tomida and Kean by using fused data from different types of sensors to determine the distance to the target and an associated confidence score as taught by Wei with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this because Wei FIG. 26 on p. 29 teaches that the fusion of multiple different sensor types can provide for more detection and accurate position estimation, and help to eliminate disadvantages associated with the use of a single sensor such as inaccurate position estimation, limited field of view, limited working conditions, and mis-detection or mis-classification.
Regarding claim 2:
The combination of Tomida, Kean, and Wei teaches “The machine of claim 1,” and Tomida further teaches “wherein the validity information indicates, for each sensor of the plurality of sensors, whether perception data that is captured by the sensor is valid.” (Tomida ¶ 54 teaches that the sensor data analysis can be performed for each sonar apparatus, and Tomida ¶ 8 teaches that the system is used for “determining whether the distance measurement value is valid or invalid based on the distance measurement value, the past distance measurement value, and movement information of the sensor.”)
Regarding claim 3:
The combination of Tomida, Kean, and Wei teaches “The machine of claim 1,” and Tomida further teaches “wherein the controller, to determine the validity information, is configured to: identify perception data, of the perception information, that is captured by a sensor of the plurality of sensors; determine, based on the perception data, a perceived distance to the target; determine a distance difference between the perceived distance and the previously determined distance; and determine, based on the distance difference, whether the perception data is valid or not valid.” (Tomida ¶ 76: “In a case where the value |dt−dt-1|/dw calculated based on the difference between distance measurement value dt and distance measurement value dt-1 is larger than the threshold, filter processor 322 determines that the distance measurement skipping has occurred. In FIG. 14, a large difference (value of Z01) between the current distance measurement value (time t5) and the one previous distance measurement value (time t4) indicates that the distance measurement value has largely changed, and therefore, it can be determined from FIG. 13 that distance measurement skipping has occurred.” Additionally, Tomida ¶ 70: “The distance measurement skipping indicates a state in which a distance measurement value that is temporarily significantly different is detected, and the target switching indicates that the target has been switched from a reflected wave from target A to a reflected wave from target B, for example.”)
Regarding claim 4:
The combination of Tomida, Kean, and Wei teaches “The machine of claim 1,” and Tomida further teaches “wherein the controller, to determine the validity information, is configured to: identify perception data, of the perception information, that is captured by a sensor of the plurality of sensors; determine, based on the perception data, a perceived distance to the target; identify a previously determined perceived distance to the target that was determined based on previously captured perception data by the sensor; determine a distance difference between the perceived distance and the previously determined perceived distance; and determine, based on the distance difference, whether the perception data is valid or not valid.” (Tomida ¶ 76: “In a case where the value |dt−dt-1|/dw calculated based on the difference between distance measurement value dt and distance measurement value dt-1 is larger than the threshold, filter processor 322 determines that the distance measurement skipping has occurred. In FIG. 14, a large difference (value of Z01) between the current distance measurement value (time t5) and the one previous distance measurement value (time t4) indicates that the distance measurement value has largely changed, and therefore, it can be determined from FIG. 13 that distance measurement skipping has occurred.” Also, Tomida ¶ 70: “The distance measurement skipping indicates a state in which a distance measurement value that is temporarily significantly different is detected, and the target switching indicates that the target has been switched from a reflected wave from target A to a reflected wave from target B, for example.”)
Regarding claim 6:
The combination of Tomida, Kean, and Wei teaches “The machine of claim 1,” and Kean further teaches “wherein the controller, to determine the validity information, is configured to: identify perception data, of the perception information, that is captured by a sensor of the plurality of sensors; determine, based on the position of the implement and the linkage, whether a field of view of the sensor is obstructed by the implement and the linkage; and determine, based on determining whether the field of view of the sensor is obstructed, whether the perception data is valid or not valid.” (Kean ¶ 7: “Referring to a wheel loader application for illustrative purposes, a system and method as disclosed herein may for example use a stereo camera to identify and measure the distance from the wheel loader to a truck or hopper.” Also, Kean ¶ 69: “the method may further include identifying, based on linkage pose or stereo measurement, when the camera view has been wholly or partially obstructed, for example by the current position of the attachment (e.g., loader bucket) and/or material heaped therein. In such a case, the controller 112 may be configured to use only alternative inputs such as the vehicle motion measurements to estimate a position of the loading area, based for example on vehicle motion since the last valid camera measurement.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the system that is disclosed by the combination of Tomida and Wei by identifying whether the sensor is obstructed by the attachment tool as taught by Kean with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this since Kean ¶ 69 teaches that when the sensor is blocked, the controller can exclude readings from that sensor and instead use readings from alternative sensors; a person having ordinary skill in the art would have recognized that this would improve sensing reliability and help the vehicle to avoid collisions.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Tomida in view of Kean and Wei as applied to claim 1 above, and further in view of Shimoda et al. (US 2019/0360176 A1), hereinafter referred to as Shimoda.
Regarding claim 5:
The combination of Tomida, Kean, and Wei teaches “The machine of claim 1,” and Tomida further teaches “wherein the controller, to determine the validity information, is configured to: identify perception data, of the perception information, that is captured by a sensor of the plurality of sensors; determine, based on the perception data, a perceived distance to the target; determine, based on other perception data, of the perception information, that is captured, respectively, by one or more other sensors of the plurality of sensors, one or more other perceived distances to the target.” (Tomida ¶ 54 and FIG. 4 disclose a process of relating a specific sensor to its distance measurement values and timestamps, and then repeating the process for each sensor.)
The combination of Tomida, Kean, and Wei does not specifically teach to “determine respective distance differences between the perceived distance and the one or more other perceived distances; and determine, based on the respective distance differences, whether the perception data is valid or not valid.” However, Shimoda does teach this limitation. (Shimoda ¶ 68: “When the predetermined object S is disposed in the first overlapping area Q1, position information of the identical target from the distance image data acquired by the first distance sensor 111 is compared to position information of the identical target from the distance image data acquired by the second distance sensor 112, so that a positional displacement of the distance sensor can be detected. … as the position of the first distance sensor 111 is checked, when ‘coordinate difference ΔD>α’ at step S4 in FIG. 7, the positional displacement detection unit 121 may determine that a positional displacement is generated in the second distance sensor 112.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the system that is disclosed by the combination of Tomida, Kean, and Wei by determining whether perception data is valid based on comparing data from two different sensors as taught by Shimoda with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this because Shimoda ¶ 81 teaches that this helps to avoid operating based on wrong recognition results, which can help the system to operate more reliably.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Tomida in view of Kean and Wei as applied to claim 1 above, and further in view of Lord et al. (US 2025/0333077 A1), hereinafter referred to as Lord.
Regarding claim 7:
The combination of Tomida, Kean, and Wei teaches “The machine of claim 1,” and Tomida further teaches “wherein the controller, to determine the validity information, is configured to: identify perception data, of the perception information, that is captured by a sensor of the plurality of sensors; identify a first instant in time associated with the previously determined distance; identify a second instant in time associated with the perception data.” (Tomida ¶¶ 77-78 and FIGS. 15-16 disclose an analysis of distance measurement values at different timestamps for one of the sensors.)
The combination of Tomida, Kean, and Wei does not specifically teach to “determine whether the second instant in time occurred after the first instant in time; and determine, based on determining whether the second instant in time occurred after the first instant in time, whether the perception data is valid or not valid.” However, Lord does teach this limitation. (Lord ¶ 81: “nominal path trajectories may be outdated because they are generated using perception data received at a first time (e.g., time t−1), while the fast path trajectories are generated using perception data received at a second time after the first time (e.g., time t−0.5).”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the system that is disclosed by the combination of Tomida, Kean, and Wei by determining whether perception data is outdated based on whether the timestamp occurs after another timestamp as taught by Lord with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this because Lord ¶ 39 teaches that this can help to avoid making operation decisions based on outdated data, thereby improving operation safety.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Tomida in view of Kean and Wei as applied to claim 1 above, and further in view of Giovanardi et al. (US 2022/0324421 A1), hereinafter referred to as Giovanardi.
Regarding claim 8:
The combination of Tomida, Kean, and Wei teaches “The machine of claim 1,” and Tomida further teaches “wherein the controller, to determine the validity information, is configured to: identify perception data, of the perception information, that is captured by a sensor of the plurality of sensors.” (Tomida ¶ 54 and FIG. 4 disclose relating sensor positions with distance measurement values captured by each of the sensors.)
The limitations below are not specifically taught by the combination of Tomida, Kean, and Wei, but are taught by Giovanardi:
“determine, based on the steering angle of the machine, a projected path of the machine.” (Giovanardi ¶ 213: “selection of the desired angle may be guided at least in part by looking at a projected trajectory of the vehicle, using for example a model based on steering angle, speed, yaw rate and/or lateral acceleration measurements and/or model states, for example using a bicycle model or a Kalman filter.”)
“determine whether the perception data is associated with the projected path; and determine, based on determining whether the perception data is associated with the projected path, whether the perception data is valid or not valid.” (Giovanardi ¶ 236: “The vehicle 1801 is equipped with a range sensor 1806 that is configured to measure distance from an object straight ahead of the vehicle, following direction 1805, and at a different angle ahead of the vehicle, following direction 1807. … Using a terrain-based ADAS feature configured to precisely predict the curvature of the roadway ahead of the vehicle, and/or the path the vehicle is likely to take based on information from a database including terrain-based information, the system is configured to alert the driver that the sensor reading may be inaccurate.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the system that is disclosed by the combination of Tomida, Kean, and Wei by determining whether the perception data is valid based upon a projected path of the vehicle as taught by Giovanardi with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this because Giovanardi ¶ 236 teaches that this can be used to alert the driver of inaccurate sensor readings; a person having ordinary skill in the art would have recognized that alerting the driver in this way would improve driving efficiency and help with avoiding potential collisions.
Claims 9-11, 16-17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Tomida et al. (US 2025/0306202 A1), hereinafter referred to as Tomida, in view of Wei et al. (the non-patent article “LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System”), hereinafter referred to as Wei.
Regarding claim 9:
Tomida discloses the following limitations:
“A controller of a machine, comprising: one or more memories; and one or more processors, coupled to the one or more memories, configured to: identify a previously determined distance to a target.” (Tomida ¶ 8 discloses that “A vehicle according to an embodiment of the present disclosure includes a processing apparatus according to an embodiment of the present disclosure includes: a processor; and a memory having instructions that, when executed by the processor, cause the processor to perform operations comprising: inputting a distance measurement value and a past distance measurement value are input, the distance measurement value indicating a distance to a target object measured by a sensor at a first time point, the past distance measurement value indicating a distance to the target object measured by the sensor at one or more time points earlier than the first time point.”)
“obtain machine information from a machine sensor system of the machine.” (Tomida ¶¶ 34 and 40 disclose that the vehicle can include several groups of sonar sensors, and further discloses that the vehicle can perform autonomous functions, which implies the use of machine sensors to obtain data to assist in controlling the vehicle.)
“obtain perception information from a perception sensor system of the machine that includes a plurality of sensors.” (Tomida ¶¶ 32-34: “sonar apparatus 100 is an apparatus that transmits an ultrasonic signal, receives an ultrasonic signal reflected by a target object (object), and performs detection of the target or the like. … Each sonar apparatus 100 includes one sensor 120, but may include a plurality of sensors 120. … Controller 110 outputs the detection result of the target object to a vehicle control apparatus (Electronic Control Unit: ECU).” Further, Tomida ¶¶ 40-41: “In FIG. 2, vehicle 200 includes sonar apparatuses 207 to 218… As sonar apparatuses 207 to 218, sonar apparatus 100 in FIG. 1 is used, for example. Further, the number and arrangement of the sonar apparatuses are not limited to those illustrated in FIG. 2.” Additionally, Tomida ¶ 44: “In a case where processing apparatus 320 is controller 110, peripheral monitoring sensor 310 is sensor 120. In a case where processing apparatus 320 is ECU 230, peripheral monitoring sensor 310 is sonar apparatus 100.”)
“determine, based on at least one of the previously determined distance to the target or the machine information, validity information associated with the perception information; select, based on the validity information, a portion of the perception information that includes perception data… indicated by the validity information as valid, and that excludes perception data … indicated by the validity information as not valid; determine, based on the portion of the perception information, a current distance to the target.” (Tomida ¶ 76: “In a case where the value |dt−dt-1|/dw calculated based on the difference between distance measurement value dt and distance measurement value dt-1 is larger than the threshold, filter processor 322 determines that the distance measurement skipping has occurred. In FIG. 14, a large difference (value of Z01) between the current distance measurement value (time t5) and the one previous distance measurement value (time t4) indicates that the distance measurement value has largely changed, and therefore, it can be determined from FIG. 13 that distance measurement skipping has occurred.” Also, Tomida ¶ 70: “The distance measurement skipping indicates a state in which a distance measurement value that is temporarily significantly different is detected, and the target switching indicates that the target has been switched from a reflected wave from target A to a reflected wave from target B, for example.” This at least teaches to determine validity information based on “the previously determined distance to the target” as claimed. Note that the range of values below the threshold correspond to the “portion of the perception information.”)
“and cause, based on the current distance to the target, an automatic control operation associated with at least one of movement of the machine or movement of an implement and a linkage of the machine relative to the target.” (Tomida ¶ 7 discloses “determining whether the distance measurement value is valid or invalid based on the distance measurement value, the past distance measurement value, and movement information of the sensor; and outputting a control signal for controlling a controller of a vehicle on which the sensor is mounted based on a result of the determination.” Also, Tomida ¶ 51: “Collision determinator 330 determines whether the host vehicle will collide with the target based on the generated coordinates. In a case where collision determinator 330 determines that there is a possibility of the vehicle colliding with the target, collision determinator 330 performs control to avoid the collision by outputting it to a brake or a vehicle steering section (not illustrated) to operating an emergency brake or operate a steering wheel.” This at least teaches to cause an automatic control operation associated with “movement of the machine” as claimed.)
Note that under the broadest reasonable interpretation (BRI) of claim 9, consistent with the instant specification, the recited steps to “determine, based on at least one of the previously determined distance to the target or the machine information, validity information associated with the perception information” and to “cause, based on the current distance to the target, an automatic control operation associated with at least one of movement of the machine or movement of the implement and the linkage relative to the target” are each being treated as an alternative limitation. Applicant has elected to use the phrase “at least one” in the claim language, and as such, the BRI covers the scenario in which only one of the limitations applies. Therefore, while only the “the previously determined distance to the target” and the “movement of the machine” have been addressed here, the claim is still rejected in its entirety.
Tomida does not explicitly disclose to consider the validity of the perception information “captured by at least two different types of sensors of the plurality of sensors” and determine the current distance to the target “as a representative fused distance to the target based on distances associated with the perception data captured by the at least two different types of sensors.” However, Wei does teach these limitations. (Wei p. 5 last two paragraphs: “In this system, we first obtain images from the camera, then through the camera object detection system, we estimate the bounding box coordinates of beacons together with the confidence scores for each bounding box. Next, the detection bounding box from the single camera is mapped through a neural network (NN) into a distance and angle estimate, in order to be able to fuse that information with the distance and angle estimates of the LiDAR processing. On the other side, we have point cloud information from the LiDAR, then through LiDAR data processing, we estimate the distance and angle information of the detected beacons by the LiDAR. Through the LiDAR processing, we also obtain a pseudo-confidence score. With the LiDAR detection results in the form of distance and angle from both the camera and LiDAR, we fuse them together to obtain a final distance, angle and confidence score for each detection.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the system of Tomida by using fused data from different types of sensors to determine the distance to the target and an associated confidence score as taught by Wei with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this since Wei FIG. 26 on p. 29 teaches that the fusion of multiple different sensor types can provide for more detection and accurate position estimation, and help to eliminate disadvantages associated with the use of a single sensor such as inaccurate position estimation, limited field of view, limited working conditions, and mis-detection or mis-classification.
Regarding claim 10:
The combination of Tomida and Wei teaches “The controller of claim 9,” and Tomida further teaches “wherein the one or more processors, to determine the validity information, are configured to: determine, based on perception data, of the perception information, that is captured by a sensor of the plurality of sensors, a perceived distance to the target; determine a distance difference between the perceived distance and the previously determined distance; and determine, based on the distance difference, whether the perception data is valid or not valid.” (Tomida ¶ 76: “In a case where the value |dt−dt-1|/dw calculated based on the difference between distance measurement value dt and distance measurement value dt-1 is larger than the threshold, filter processor 322 determines that the distance measurement skipping has occurred. In FIG. 14, a large difference (value of Z01) between the current distance measurement value (time t5) and the one previous distance measurement value (time t4) indicates that the distance measurement value has largely changed, and therefore, it can be determined from FIG. 13 that distance measurement skipping has occurred.” Also, Tomida ¶ 70: “The distance measurement skipping indicates a state in which a distance measurement value that is temporarily significantly different is detected, and the target switching indicates that the target has been switched from a reflected wave from target A to a reflected wave from target B, for example.”)
Regarding claim 11:
The combination of Tomida and Wei teaches “The controller of claim 9,” and Tomida further teaches “wherein the one or more processors, to determine the validity information, are configured to: determine, based on perception data, of the perception information, that is captured by a sensor of the plurality of sensors, a perceived distance to the target; identify a previously determined perceived distance to the target that was determined based on previously captured perception data by the sensor; determine a distance difference between the perceived distance and the previously determined perceived distance; and determine, based on the distance difference, whether the perception data is valid or not valid.” (Tomida ¶ 76: “In a case where the value |dt−dt-1|/dw calculated based on the difference between distance measurement value dt and distance measurement value dt-1 is larger than the threshold, filter processor 322 determines that the distance measurement skipping has occurred. In FIG. 14, a large difference (value of Z01) between the current distance measurement value (time t5) and the one previous distance measurement value (time t4) indicates that the distance measurement value has largely changed, and therefore, it can be determined from FIG. 13 that distance measurement skipping has occurred.” Also, Tomida ¶ 70: “The distance measurement skipping indicates a state in which a distance measurement value that is temporarily significantly different is detected, and the target switching indicates that the target has been switched from a reflected wave from target A to a reflected wave from target B, for example.”)
Regarding claim 16:
Tomida discloses the following limitations:
“A method, comprising: obtaining, by a controller of a machine, perception information.” (Tomida ¶ 8: “A vehicle according to an embodiment of the present disclosure includes a processing apparatus according to an embodiment of the present disclosure includes: a processor; and a memory having instructions that, when executed by the processor, cause the processor to perform operations comprising: inputting a distance measurement value and a past distance measurement value are input, the distance measurement value indicating a distance to a target object measured by a sensor at a first time point, the past distance measurement value indicating a distance to the target object measured by the sensor at one or more time points earlier than the first time point.” Also, Tomida ¶ 34: “Controller 110 outputs the detection result of the target object to a vehicle control apparatus (Electronic Control Unit: ECU).”)
“from a perception sensor system of the machine that includes a plurality of sensors, wherein the perception information includes respective perception data captured by … the plurality of sensors.” (Tomida ¶¶ 32-33: “sonar apparatus 100 is an apparatus that transmits an ultrasonic signal, receives an ultrasonic signal reflected by a target object (object), and performs detection of the target or the like. … Each sonar apparatus 100 includes one sensor 120, but may include a plurality of sensors 120.” Also, Tomida ¶¶ 40-41: “In FIG. 2, vehicle 200 includes sonar apparatuses 207 to 218… As sonar apparatuses 207 to 218, sonar apparatus 100 in FIG. 1 is used, for example. Further, the number and arrangement of the sonar apparatuses are not limited to those illustrated in FIG. 2.” Also, Tomida ¶ 44: “In a case where processing apparatus 320 is controller 110, peripheral monitoring sensor 310 is sensor 120. In a case where processing apparatus 320 is ECU 230, peripheral monitoring sensor 310 is sonar apparatus 100.”)
“determining, by the controller, validity information associated with the perception information; selecting, by the controller, based on the validity information, a portion of the perception information that includes perception data … indicated by the validity information as valid, and that excludes perception data … indicated by the validity information as not valid; determining, by the controller, based on the portion of the perception information, a current distance to a target.” (Tomida ¶ 76: “In a case where the value |dt−dt-1|/dw calculated based on the difference between distance measurement value dt and distance measurement value dt-1 is larger than the threshold, filter processor 322 determines that the distance measurement skipping has occurred. In FIG. 14, a large difference (value of Z01) between the current distance measurement value (time t5) and the one previous distance measurement value (time t4) indicates that the distance measurement value has largely changed, and therefore, it can be determined from FIG. 13 that distance measurement skipping has occurred.” Also, Tomida ¶ 70: “The distance measurement skipping indicates a state in which a distance measurement value that is temporarily significantly different is detected, and the target switching indicates that the target has been switched from a reflected wave from target A to a reflected wave from target B, for example.”)
“and causing, based on the current distance to the target, an automatic control operation associated with at least one of movement of the machine or movement of an implement and a linkage of the machine relative to the target.” (Tomida ¶ 7 discloses “determining whether the distance measurement value is valid or invalid based on the distance measurement value, the past distance measurement value, and movement information of the sensor; and outputting a control signal for controlling a controller of a vehicle on which the sensor is mounted based on a result of the determination.” Also, Tomida ¶ 51: “Collision determinator 330 determines whether the host vehicle will collide with the target based on the generated coordinates. In a case where collision determinator 330 determines that there is a possibility of the vehicle colliding with the target, collision determinator 330 performs control to avoid the collision by outputting it to a brake or a vehicle steering section (not illustrated) to operating an emergency brake or operate a steering wheel.” This at least teaches to cause an automatic control operation associated with “movement of the machine” as claimed.)
Note that under the broadest reasonable interpretation (BRI) of claim 16, consistent with the instant specification, the recited step of “causing, based on the current distance to the target, an automatic control operation associated with at least one of movement of the machine or movement of an implement and a linkage of the machine relative to the target” is treated as an alternative limitation. Applicant has elected to use the phrase “at least one” in the claim language, and as such, the BRI covers the scenario in which only one of the limitations applies. Therefore, while only the “movement of the machine” has been addressed here, the claim is still rejected in its entirety.
Tomida does not specifically disclose that “the perception information includes respective perception data captured by at least two different types of sensors” and to consider the validity of the perception information “captured by the at least two different types of sensors” and to determine the current distance to the target “as a representative fused distance to the target based on distances associated with the perception data captured by the at least two different types of sensors.” However, Wei does teach these limitations. (Wei p. 5 last two paragraphs: “In this system, we first obtain images from the camera, then through the camera object detection system, we estimate the bounding box coordinates of beacons together with the confidence scores for each bounding box. Next, the detection bounding box from the single camera is mapped through a neural network (NN) into a distance and angle estimate, in order to be able to fuse that information with the distance and angle estimates of the LiDAR processing. On the other side, we have point cloud information from the LiDAR, then through LiDAR data processing, we estimate the distance and angle information of the detected beacons by the LiDAR. Through the LiDAR processing, we also obtain a pseudo-confidence score. With the LiDAR detection results in the form of distance and angle from both the camera and LiDAR, we fuse them together to obtain a final distance, angle and confidence score for each detection.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the method of Tomida by using fused data from different types of sensors to determine the distance to the target and an associated confidence score as taught by Wei with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this since Wei FIG. 26 on p. 29 teaches that the fusion of multiple different sensor types can provide for more detection and accurate position estimation, and help to eliminate disadvantages associated with the use of a single sensor such as inaccurate position estimation, limited field of view, limited working conditions, and mis-detection or mis-classification.
Regarding claim 17:
The combination of Tomida and Wei teaches “The method of claim 16,” and Tomida further teaches the following limitations:
“further comprising: determining, based on perception data, of the perception information, that is captured by a sensor of the plurality of sensors, a perceived distance to the target.” (Tomida ¶ 76 and FIG. 14 disclose analysis of measurement values d1-d9 each representing a detected distance to a target from a sensor.)
“determining distance difference information, which indicates at least one of: a first distance difference between the perceived distance and a previously determined distance to the target, a second distance difference between the perceived distance and a previously determined perceived distance to the target that was determined based on previously captured perception data by the sensor, or respective third distance differences between the perceived distance and one or more other perceived distances to the target that are determined based on other perception data, of the perception information, that is captured, respectively, by one or more other sensors of the plurality of sensors.” (Tomida ¶ 76: “In a case where the value |dt−dt-1|/dw calculated based on the difference between distance measurement value dt and distance measurement value dt-1 is larger than the threshold, filter processor 322 determines that the distance measurement skipping has occurred. In FIG. 14, a large difference (value of Z01) between the current distance measurement value (time t5) and the one previous distance measurement value (time t4) indicates that the distance measurement value has largely changed, and therefore, it can be determined from FIG. 13 that distance measurement skipping has occurred.” This at least teaches to determine distance difference information indicating “a second distance difference between the perceived distance and a previously determined perceived distance to the target that was determined based on previously captured perception data by the sensor” as claimed.)
“and determining, based on the distance difference information, whether the perception data is valid or not valid.” (Tomida ¶¶ 70 and 76 disclose identification of skipping, where “The distance measurement skipping indicates a state in which a distance measurement value that is temporarily significantly different is detected, and the target switching indicates that the target has been switched from a reflected wave from target A to a reflected wave from target B, for example.”)
Note that under the broadest reasonable interpretation (BRI) of claim 17, consistent with the instant specification, the distance difference information indicating “at least one of: a first distance difference between the perceived distance and a previously determined distance to the target, a second distance difference between the perceived distance and a previously determined perceived distance to the target that was determined based on previously captured perception data by the sensor, or respective third distance differences between the perceived distance and one or more other perceived distances to the target that are determined based on other perception data, of the perception information, that is captured, respectively, by one or more other sensors of the plurality of sensors” is treated as an alternative limitation. Applicant has elected to use the phrase “at least one” in the claim language, and therefore, the BRI covers the scenario in which only one of the limitations applies. Therefore, while only the “second distance difference” has been addressed here, the claim is still rejected in its entirety.
Regarding claim 19:
The combination of Tomida and Wei teaches “The method of claim 16,” and Tomida further discloses the method “further comprising: identifying perception data, of the perception information, that is captured by a sensor of the plurality of sensors; and determining, based on an instant in time associated with the perception data, whether the perception data is valid or not valid.” (Tomida ¶¶ 77-78 and FIGS. 15-16 disclose identification of target switching based on an analysis of distance measurement values at different timestamps for one of the sensors.)
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Tomida in view of Wei as applied to claim 9 above, and further in view of Shimoda et al. (US 2019/0360176 A1), hereinafter referred to as Shimoda.
Regarding claim 12:
Claim 12 is rejected with the same rationale applied to claim 5 above, mutatis mutandis.
Claims 13 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Tomida in view of Wei as applied to claims 9 and 16 above, and further in view of Kean et al. (US 2022/0333344 A1), hereinafter referred to as Kean.
Regarding claim 13:
The combination of Tomida and Wei teaches “The controller of claim 9,” but does not specifically teach “wherein the one or more processors, to determine the validity information, are configured to: identify perception data, of the perception information, that is captured by a sensor of the plurality of sensors; determine, based on the machine information, whether a field of view of the sensor is obstructed; and determine, based on determining whether the field of view of the sensor is obstructed, whether the perception data is valid or not valid.” However, Kean does teach these limitations. (Kean ¶ 7: “Referring to a wheel loader application for illustrative purposes, a system and method as disclosed herein may for example use a stereo camera to identify and measure the distance from the wheel loader to a truck or hopper.” Also, Kean ¶ 69: “the method may further include identifying, based on linkage pose or stereo measurement, when the camera view has been wholly or partially obstructed, for example by the current position of the attachment (e.g., loader bucket) and/or material heaped therein. In such a case, the controller 112 may be configured to use only alternative inputs such as the vehicle motion measurements to estimate a position of the loading area, based for example on vehicle motion since the last valid camera measurement.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the system that is disclosed by the combination of Tomida and Wei by identifying whether a sensor is obstructed by an attachment tool as taught by Kean with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this because Kean ¶ 69 teaches that when the sensor is blocked, then the controller can exclude readings from that sensor and instead use readings from alternative sensors; a person having ordinary skill in the art would have recognized that this would improve sensing reliability and help the vehicle to avoid collisions.
Regarding claim 18:
Claim 18 is rejected with the same rationale applied to claim 13 above, mutatis mutandis.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Tomida in view of Wei as applied to claim 9 above, and further in view of Lord et al. (US 2025/0333077 A1), hereinafter referred to as Lord.
Regarding claim 14:
Claim 14 is rejected with the same rationale applied to claim 7 above, mutatis mutandis.
Claims 15 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Tomida in view of Wei as applied to claims 9 and 16 above, and further in view of Giovanardi et al. (US 2022/0324421 A1), hereinafter referred to as Giovanardi.
Regarding claim 15:
The combination of Tomida and Wei teaches “The controller of claim 9,” and Tomida also teaches “wherein the one or more processors, to determine the validity information, are configured to: identify perception data, of the perception information, that is captured by a sensor of the plurality of sensors.” (Tomida ¶ 54 and FIG. 4 disclose relating sensor positions with distance measurement values captured by each of the sensors.)
The combination of Tomida and Wei does not specifically teach to “determine, based on the machine information, whether the perception data is associated with a projected path of the machine; and determine, based on determining whether the perception data is associated with the projected path, whether the perception data is valid or not valid.” However, Giovanardi does teach these limitations. (Giovanardi ¶ 236: “The vehicle 1801 is equipped with a range sensor 1806 that is configured to measure distance from an object straight ahead of the vehicle, following direction 1805, and at a different angle ahead of the vehicle, following direction 1807. … Using a terrain-based ADAS feature configured to precisely predict the curvature of the roadway ahead of the vehicle, and/or the path the vehicle is likely to take based on information from a database including terrain-based information, the system is configured to alert the driver that the sensor reading may be inaccurate.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the system that is disclosed by the combination of Tomida and Wei by determining whether the perception data is valid based on a projected path of the vehicle as taught by Giovanardi with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this because Giovanardi ¶ 236 teaches that this can be used to alert the driver of inaccurate sensor readings; a person having ordinary skill in the art would have recognized that alerting the driver in this way would improve driving efficiency and help with avoiding potential collisions.
Regarding claim 20:
Claim 20 is rejected with the same rationale applied to claim 15 above, mutatis mutandis.
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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/Madison R. Inserra/Primary Examiner, Art Unit 3662
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