DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. 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.
Information Disclosure Statement
3. The Information Disclosure Statement filed 2 February 2026 has been fully considered by Examiner. An annotated copy is included herewith. Foreign Patent Document 2 has been struck through since there is no copy of the reference in the application. Examiner further notes that CN-106529081-A is present in the application, but is not cited in any Information Disclosure Statement.
Claim Rejections - 35 USC § 102
4. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
5. Claims 1-3, 6, 11-13 and 16 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Miller (US-11,124,947).
Regarding claim 1: Miller discloses a method for automated monitoring of volumetric properties of work pile mounds (fig 5; and column 9, line 48 to column 10, line 15 of Miller – monitors machine and updates parameters based on automated monitoring of work piles, including volumetric properties obtained from 3D image data, distance sensors, and so on), comprising: obtaining monitoring sensor data of a surrounding environment which includes one or more work pile mounds (fig 2(195); column 3, lines 29-32; and column 4, lines 3-13 of Miller), wherein the monitoring data comprises depth sensor data (fig 2(240,295); and column 5, lines 43-59 of Miller – distance/depth computed for work pile) and motion sensor data (fig 1(170,380); fig 2(170,195); column 3, lines 23-32; column 5, lines 41-55; and column 8, lines 32-42 of Miller – sensor-augmented guidance which adjusts work machine parameters when the work machine moves to engage with the work pile); generating, based on the monitoring data, a three-dimensional (3D) construction of the surrounding environment (column 5, line 63 to column 6, line 27 of Miller – set of 3D points in the collected image data, along with edge detection, image correction, and other processes to generate a 3D construction of the surrounding environment); determining, based on the 3D construction, at least one volumetric property of a work pile mound in a target area (column 6, lines 20-27; and column 6, line 53 to column 7, line 4 of Miller – edges, materials, load parameters and other volumetric properties of the work pile); and generating an output that includes the determined volumetric properties (column 7, line 18 to column 8, line 6 of Miller – determined volumetric properties output for use in control of the work machine).
Regarding claim 2: Miller discloses the method of claim 1 (as rejected above), wherein the depth sensor data comprises point cloud data (column 5, line 67 to column 6, line 7 of Miller – set of 3D points corresponding to pixel positions of the image data, and thus point cloud data), and the motion sensor data comprises relative position data (column 5, lines 41-47 of Miller – distance from sensor/work machine, and thus relative position).
Regarding claim 3: Miller discloses the method of claim 1 (as rejected above), wherein the monitoring data is generated by a sensor subsystem of a monitoring system (column 5, lines 16-26 of Miller), wherein the monitoring system is coupled to a ground vehicle (fig 1 and column 3, lines 23-25 of Miller).
Regarding claim 6: Miller discloses the method of claim 1 (as rejected above), wherein the work pile mound comprises a heap or a pile of material or objects, including heaps or piles of dirt, rock, gravel, asphalt or any other loose rock material (column 3, lines 58-64 of Miller).
Regarding claim 11: Miller discloses a monitoring system (fig 2 and column 4, lines 14-17 of Miller) for automated monitoring of volumetric properties of work pile mounds (fig 5; and column 9, line 48 to column 10, line 15 of Miller – monitors machine and updates parameters based on automated monitoring of work piles, including volumetric properties obtained from 3D image data, distance sensors, and so on), comprising: a sensor subsystem for generating monitoring sensor data (fig 2(170) and column 4, lines 9-13 of Miller); and at least one processor coupled to the sensor subsystem (fig 2(195) and column 5, lines 16-20 of Miller) and configured for: obtaining monitoring sensor data of a surrounding environment which includes one or more work pile mounds (fig 2(195); column 3, lines 29-32; and column 4, lines 3-13 of Miller), wherein the monitoring sensor data comprises depth sensor data (fig 2(240, 295); and column 5, lines 43-59 of Miller – distance/depth computed for work pile) and motion sensor data generated by the sensor subsystem (fig 1(170,380); fig 2(170, 195); column 3, lines 23-32; column 5, lines 41-55; and column 8, lines 32-42 of Miller – sensor-augmented guidance which adjusts work machine parameters when the work machine moves to engage with the work pile); generating, based on the monitoring data, a three-dimensional (3D) construction of the surrounding environment (column 5, line 63 to column 6, line 27 of Miller – set of 3D points in the collected image data, along with edge detection, image correction, and other processes to generate a 3D construction of the surrounding environment); determining, based on the 3D construction, at least one volumetric property of a work pile mound in a target area (column 6, lines 20-27; and column 6, line 53 to column 7, line 4 of Miller – edges, materials, load parameters and other volumetric properties of the work pile); and generating an output that includes the determined volumetric properties (column 7, line 18 to column 8, line 6 of Miller – determined volumetric properties output for use in control of the work machine).
Regarding claim 12: Miller discloses the system of claim 11 (as rejected above), wherein the depth sensor data comprises point cloud data (column 5, line 67 to column 6, line 7 of Miller – set of 3D points corresponding to pixel positions of the image data, and thus point cloud data), and the motion sensor data comprises relative position data (column 5, lines 41-47 of Miller – distance from sensor/work machine, and thus relative position).
Regarding claim 13: Miller discloses the system of claim 11 (as rejected above), wherein the monitoring system is couplable to a ground vehicle (fig 1 and column 3, lines 23-25 of Miller).
Regarding claim 16: Miller discloses the system of claim 11 (as rejected above), wherein the work pile mound comprises a heap or a pile of material or objects, including heaps or piles of dirt, rock, gravel, asphalt or any other loose rock material (column 3, lines 58-64 of Miller).
Claim Rejections - 35 USC § 103
6. 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.
7. Claims 4, 5, 14 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Miller (US-11,124,947) in view of Hodel (US-2024/0328125).
Regarding claim 4: Miller discloses the method of claim 3 (as rejected above). Miller does not disclose wherein the sensor subsystem comprises a time of flight (ToF) sensor for generating the depth sensor data, and an inertial measurement unit (IMU) for generating the motion sensor data.
Hodel discloses wherein the sensor subsystem comprises a time of flight (ToF) sensor for generating the depth sensor data ([0026] of Hodel – “3D sensor(s) 158 may comprise a RADAR system, a LIDAR system, a time-of-flight camera”), and an inertial measurement unit (IMU) for generating the motion sensor data ([0022] of Hodel – “sensor 152 may comprise an inertial measurement unit (IMU)”).
Miller and Hodel are analogous art because they are from the same field of endeavor, namely 3D imaging for environment and terrain analysis for construction and excavation vehicles. Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have the sensor subsystem comprise a time of flight (ToF) sensor for generating the depth sensor data, and an inertial measurement unit (IMU) for generating the motion sensor data, as taught by Hodel. The suggestion for doing so would have been that ToF sensors and IMUs are common and effective types of sensors for generating the data needed in Miller. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Miller according to the relied-upon teachings of Hodel to obtain the invention as specified in claim 4.
Regarding claim 5: Miller discloses the method of claim 3 (as rejected above). Miller does not disclose wherein the vehicle follows a vehicle path around a work pile mound.
Hodel discloses wherein the vehicle follows a vehicle path around a work pile mound ([0063] and [0069] of Hodel – can toggle on avoidance zones, including piles of material).
Miller and Hodel are analogous art because they are from the same field of endeavor, namely 3D imaging for environment and terrain analysis for construction and excavation vehicles. Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have the vehicle follow a vehicle path around a work pile, as taught by Hodel. The motivation for doing so would have been to improve safety by allowing the work machine to avoid dangerous and/or undesirable work piles. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Miller according to the relied-upon teachings of Hodel to obtain the invention as specified in claim 5.
Regarding claim 14: Miller discloses the system of claim 13 (as rejected above). Miller does not disclose wherein the vehicle follows a vehicle path around a work pile mound.
Hodel discloses wherein the vehicle follows a vehicle path around a work pile mound ([0063] and [0069] of Hodel – can toggle on avoidance zones, including piles of material).
Miller and Hodel are analogous art because they are from the same field of endeavor, namely 3D imaging for environment and terrain analysis for construction and excavation vehicles. Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have the vehicle follow a vehicle path around a work pile, as taught by Hodel. The motivation for doing so would have been to improve safety by allowing the work machine to avoid dangerous and/or undesirable work piles. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Miller according to the relied-upon teachings of Hodel to obtain the invention as specified in claim 14.
Regarding claim 15: Miller discloses the system of claim 11 (as rejected above). Miller does not disclose wherein the sensor subsystem comprises a time of flight (ToF) sensor for generating the depth sensor data, and an inertial measurement unit (IMU) for generating the motion sensor data.
Hodel discloses wherein the sensor subsystem comprises a time of flight (ToF) sensor for generating the depth sensor data ([0026] of Hodel – “3D sensor(s) 158 may comprise a RADAR system, a LIDAR system, a time-of-flight camera”), and an inertial measurement unit (IMU) for generating the motion sensor data ([0022] of Hodel – “sensor 152 may comprise an inertial measurement unit (IMU)”).
Miller and Hodel are analogous art because they are from the same field of endeavor, namely 3D imaging for environment and terrain analysis for construction and excavation vehicles. Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have the sensor subsystem comprise a time of flight (ToF) sensor for generating the depth sensor data, and an inertial measurement unit (IMU) for generating the motion sensor data, as taught by Hodel. The suggestion for doing so would have been that ToF sensors and IMUs are common and effective types of sensors for generating the data needed in Miller. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Miller according to the relied-upon teachings of Hodel to obtain the invention as specified in claim 15.
8. Claims 7, 8, 17 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Miller (US-11,124,947) in view of Sequeira (US-2018/0075643).
Regarding claim 7: Miller discloses the method of claim 1 (as rejected above), wherein generating the 3D construction of the surrounding environment comprises: processing the depth sensor data to extract depth feature data including edge and planar features (column 6, lines 20-26; and column 6, line 53 to column 7, line 4 of Miller); identifying one or more work pile mounds based on the extracted edge features (column 6, line 58 to column 7, line 4 of Miller).
Miller does not disclose based on the motion sensor data and depth sensor data, applying a simultaneous localization and mapping (SLAM) technique, using a LiDAR-inertial odometry technique, to generate the 3D reconstruction of the environment which includes the relative positioning of the work pile mounds in the surrounding environment.
Sequeira discloses based on the motion sensor data and depth sensor data, applying a simultaneous localization and mapping (SLAM) technique, using a LiDAR-inertial odometry technique, to generate the 3D reconstruction of the environment which includes the relative positioning of the objects in the surrounding environment ([0007]-[0008], and [0095]-[0096] of Sequeira – SLAM using LiDAR odometry used to generate the 3D model of the environment).
Miller and Sequeira are analogous art because they are from similar problem solving areas, namely 3D digital image modeling of an environment. Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to based on the motion sensor data and depth sensor data, applying a simultaneous localization and mapping (SLAM) technique, using a LiDAR-inertial odometry technique, to generate the 3D reconstruction of the environment which includes the relative positioning of the objects in the surrounding environment, as taught by Sequeira. By combination with Miller, the objects would specifically be work pile mounds. The motivation for doing so would have been to use an effective and efficient means for determining where possible obstructions are in the environment, thus improving overall safety. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Miller according to the relied-upon teachings of Sequeira to obtain the invention as specified in claim 7.
Regarding claim 8: Miller in view of Sequeira discloses the method of claim 7 (as rejected above), further comprising transforming the extracted depth features into a global reference frame using location sensor data (column 5, line 63 to column 6, line 19 of Miller).
Regarding claim 17: Miller discloses the system of claim 11 (as rejected above), wherein generating the 3D construction of the surrounding environment comprises the at least one processor being further configured for: processing the depth sensor data to extract depth feature data including edge and planar features (column 6, lines 20-26; and column 6, line 53 to column 7, line 4 of Miller); identifying one or more work pile mounds based on the extracted edge features (column 6, line 58 to column 7, line 4 of Miller).
Miller does not disclose based on the motion sensor data and depth sensor data, applying a simultaneous localization and mapping (SLAM) technique, using a LiDAR-inertial odometry technique, to generate the 3D reconstruction of the environment which includes the relative positioning of the work pile mounds in the surrounding environment.
Sequeira discloses based on the motion sensor data and depth sensor data, applying a simultaneous localization and mapping (SLAM) technique, using a LiDAR-inertial odometry technique, to generate the 3D reconstruction of the environment which includes the relative positioning of the objects in the surrounding environment ([0007]-[0008], and [0095]-[0096] of Sequeira – SLAM using LiDAR odometry used to generate the 3D model of the environment).
Miller and Sequeira are analogous art because they are from similar problem solving areas, namely 3D digital image modeling of an environment. Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to based on the motion sensor data and depth sensor data, applying a simultaneous localization and mapping (SLAM) technique, using a LiDAR-inertial odometry technique, to generate the 3D reconstruction of the environment which includes the relative positioning of the objects in the surrounding environment, as taught by Sequeira. By combination with Miller, the objects would specifically be work pile mounds. The motivation for doing so would have been to use an effective and efficient means for determining where possible obstructions are in the environment, thus improving overall safety. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Miller according to the relied-upon teachings of Sequeira to obtain the invention as specified in claim 17.
Regarding claim 18: Miller in view of Sequeira discloses the system of claim 17 (as rejected above), further comprising the at least one processor being further configured for: transforming the extracted depth features into a global reference frame using location sensor data (column 5, line 63 to column 6, line 19 of Miller).
Allowable Subject Matter
9. Claims 9, 10, 19 and 20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to James A Thompson whose telephone number is (571)272-7441. The examiner can normally be reached M-F 8am-6pm.
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/JAMES A THOMPSON/Primary Examiner, Art Unit 2615
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