Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 7/14/2025, 10/03/2025, 10/14/2025, 06/03/2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 102
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 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.
Claim(s) 17 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ready-Campbell, et al., hereinafter Ready (U.S. Patent Application Pub. No. 2022/0282451).
Regarding Claim 17, Ready teaches: A method (Ready, Para. 0001 – “a method for… autonomously executing earth moving operations by an earth moving vehicle based on detected risk”) comprising:
identifying an excavation location where a construction asset is to excavate material using an attachment to the asset (Ready, Para. 0045, 0056-0057, 0067 – a “navigation engine 410” and “preparation engine 420” which provide locations in the dig site, such as “a location of earth to be moved”, or excavation location);
identifying a pile location where the construction asset is to pile the material that is excavated (Ready, Para. 0045, 0056-0057 – a “navigation engine 410” and “preparation engine 420” which provide locations in the dig site, such as “a location at which earth is to be filled”, or pile location);
obtaining point cloud data from light detection and ranging (LiDAR) sensors onboard the asset (Ready, Para. 0025, 0030, 0033 – an “earth moving system”, or asset, including “a sensor assembly 110” which includes “spatial sensors 130”, such as “a LIDAR sensor”, which output sensor data including “a three-dimensional point cloud”);
processing the point cloud data to identify terrain features and obstacles outside of the asset (Ready, Para. 0033, 0045 – “a three-dimensional point cloud representing distances… between the spatial sensors 130 and the ground surface or any objects within the field of view of each spatial sensor 130”, where “on-unit computer 120a may also process the data received from the sensor assembly 110” including “spatial sensors 130” to obtain “a real-time scan of the ground surface of the dig site around the earth moving vehicle”), and to calculate a position of a cutting edge of the attachment (Ready, Para. 0045, 0068-0072, 0088-0090 – “on-unit computer 120a may fuse data from the various sensors”, where the “position and orientation of the earth moving tool 175”, including “the leading edge of the earth moving tool”, is determined “relative to a reference orientation” such as “the ground surface , a gravity vector, or a target tool path” generated based on the “digital terrain model of the dig site” generated from data provided by “spatial sensors 130”); and
autonomously controlling the asset to excavate the material at the excavation location using the position of the cutting edge of the attachment that is calculated, to move the asset to the pile location without colliding with the obstacles and without a previously defined or calculated path between the excavation location and the pile location being obtained (Ready, Para. 0069-0071, 0093, 0108 – where the “target tool path” is determined based on “a digital terrain model of the dig site” generated from “a current physical state of the dig site generated based on the sensor data, such that the tool path is not previously defined), and to dump the material at the pile location using the point cloud data (Ready, Para. 0023, 0028, 0057, 0068-0069, 0092-0093 – “an earth moving system 100 for moving… earth autonomously or semi-autonomously from a dig site”, the earth moving system including an “earth moving tool 175”, or attachment; where the earth moving system “executes instructions (e.g., instructions encoded as a set of target tool paths) to actuate one or more tools 175 and the drive train to perform an earth moving routine, for example an earth moving routine to excavate earth from a location in a dig site, a filling routine to fill earth at a location in the dig site”, etc. based on “a digital terrain model of the dig site” obtained from “the sensor data” from “spatial sensors 130”; where a “digging engine” may determine “that the target tool path is obstructed by one or more obstacles”).
In regards to Claim 20, Ready teaches the method of Claim 17, and Ready further teaches further comprising: receiving position data from one or more than one global navigation satellite system (GNSS) receivers onboard the asset (Ready, Para. 0025, 0032, 0084, 0090 – “sensor assembly 110” of the “earth moving system” includes “position sensors 145”, such as “a global positioning system interfacing with a static local ground-based GPS node”, which provide “a position of the earth moving vehicle 115” as “a localized position within a dig site, or a global position with respect latitude/longitude, or some other external reference system”);
receiving movement data from an inertial measurement unit (IMU) onboard the asset (Ready, Para. 0025, 0032, 0035, 0084, 0090, 0120 – “sensor assembly 110” of the “earth moving system” includes “measurement sensors 125” such as “inertial measurement unit sensors” for determining “movement and position of the earth moving tool 175”); and
generating a terrain map of an area surrounding the asset by fusing the point cloud data, the position data, and the movement data (Ready, Para. 0045, 0067-0069 – “the on-unit computer 120a may fuse data from the various sensors” comprising “fusing the point clouds from various spatial sensors 130, the stitching of images from multiple imaging sensors 135, and registration of images and point clouds relative to each other or relative to data regarding an external reference frame as provided by position sensors 145”, and generating “a representation of the initial state of the dig site using sensor 170 data”, where “spatial sensors 130 record spatial data in the form of point cloud representations, imaging sensors 135 gather imaging data, and depth sensors 145 gather data describing relative locations”).
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.
Claim(s) 1-6 and 9-14 are rejected under 35 U.S.C. 103 as being unpatentable over Ready in view of Theverapperuma, et al. (U.S. Patent Application Pub. No. 2020/0394813).
Regarding Claim 1, Ready teaches: A method (Ready, Para. 0001 – “a method for… autonomously executing earth moving operations by an earth moving vehicle based on detected risk”) comprising:
receiving point cloud data from one or more than one optical sensor mounted on a construction asset having a machine guidance system (Ready, Para. 0025, 0030, 0033 – an “earth moving system”, or asset, including “a sensor assembly 110” which includes “spatial sensors 130”, such as “a LIDAR sensor”, which output sensor data such as “a three-dimensional map in the form of a three-dimensional point cloud” to a “controller”, or machine guidance system), the point cloud data representing portions of terrain and obstacles outside of the asset (Ready, Para. 0033 – “a three-dimensional point cloud representing distances between one meter and fifty meters between the spatial sensors 130 and the ground surface or any objects within the field of view of each spatial sensor 130”);
filtering the point cloud data that is received (Ready, Para. 0033, 0045 – an “on-unit computer 120a may also process the data received from the sensor assembly 110” including “spatial sensors 130”, the processing including “filtering” and “smoothing”; where the spatial sensor data outputted is “a three-dimensional point cloud”)
processing the point cloud data that is filtered to identify terrain features and obstacles (Ready, Para. 0033, 0045 – “on-unit computer 120a may also process the data received from the sensor assembly 110” including “spatial sensors 130” to obtain “a real-time scan of the ground surface of the dig site around the earth moving vehicle”, the processing comprising “fusing the point clouds from various spatial sensors 130”, the point clouds representing “distances between one meter and fifty meters between the spatial sensors 130 and the ground surface or any objects within the field of view of each spatial sensor 130”);
autonomously controlling movement of the asset and an attachment to the asset while performing one or both of excavation or material dumping at a worksite using the terrain features and the obstacles that are identified (Ready, Para. 0023, 0028, 0057, 0068-0069 – “an earth moving system 100 for moving… earth autonomously or semi-autonomously from a dig site”, the earth moving system including an “earth moving tool 175”, or attachment; where the earth moving system “executes instructions (e.g., instructions encoded as a set of target tool paths) to actuate one or more tools 175 and the drive train to perform an earth moving routine, for example an earth moving routine to excavate earth from a location in a dig site, a filling routine to fill earth at a location in the dig site”, etc. based on “a digital terrain model of the dig site” obtained from “the sensor data” from “spatial sensors 130”);
receiving position data and movement data from one or more than one position or movement sensor mounted to the asset (Ready, Para. 0025, 0032, 0035, 0084, 0090, 0120 – “sensor assembly 110” of the “earth moving system” includes “position sensors 145” which provide “a position of the earth moving vehicle 115”, where the “position and orientation of the earth moving tool 175” is tracked during “the earth moving routine at the dig location”; and “sensor assembly 110” further including “measurement sensors 125” such as “inertial measurement unit sensors” for determining “movement and position of the earth moving tool 175”);
fusing the point cloud data that is filtered, the position data, and the movement data to calculate a real-world position, orientation, and a calculated position of a cutting edge of the attachment (Ready, Para. 0045, 0068-0072, 0088-0090 – “on-unit computer 120a may fuse data from the various sensors” comprising “fusing the point clouds from various spatial sensors 130, the stitching of images from multiple imaging sensors 135, and registration of images and point clouds relative to each other or relative to data regarding an external reference frame as provided by position sensors 145”; where the “position and orientation of the earth moving tool 175”, including “the leading edge of the earth moving tool”, is determined “relative to a reference orientation” such as “the ground surface , a gravity vector, or a target tool path” generated based on the “digital terrain model of the dig site” generated from data provided by “spatial sensors 130”); and
autonomously controlling the asset to adjust the position and the orientation of the attachment to maintain the calculated position of the cutting edge of the attachment at a target grade during at least some of the movement of the asset that is autonomously controlled (Ready, Para. 0043, 0063, 0088-0090, 0121 – “earth moving engine 430 receives 650 the one or more target tool paths generated by the preparation engine 420 and positions 652 the leading edge of the earth moving tool 175 below the ground surface… guided by the operations outlined in a target tool path”, the “target tool path... includes instructions to actuate an excavation tool beneath a ground surface and to maintain the position of the earth moving tool 175” and to “adjust an orientation of a earth moving tool 175 to effectively penetrate the ground surface”; where the “earth moving vehicle 115 is designed to carry out the set of instructions of an earth moving routine either entirely autonomously or semi-autonomously”).
Ready does not fully teach filtering the point cloud data that is received based on one or more than one predetermined thresholds and applying one or more spatial filters to isolate features of the terrain from the point cloud data that is filtered.
However, Theverapperuma teaches filtering the point cloud data that is received based on one or more than one predetermined thresholds and applying one or more spatial filters to isolate features of the terrain from the point cloud data that is filtered (Theverapperuma, Para. 0012-0013, 0090-0095, 0113 – obtaining “a point cloud generated using a LIDAR or radar sensor”, using “a machine learning model that has been trained to detect pile shapes from point clouds”, and “generating the 3D representation of the pile of material”; where conditioning operations are applied to sensor data, including “operations to eliminate noise or unneeded information (e.g., cropping of images, eliminating LIDAR data captured outside of a certain field of view, removing data corresponding to objects or regions that are not of interest… etc.)”, i.e. eliminating data outside a threshold range, and identifying “instances” of objects, for example “pile #1, pile #2”, such that the features are isolated).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Ready to include filtering the point cloud data that is received based on one or more than one predetermined thresholds and applying one or more spatial filters to isolate features of the terrain from the point cloud data that is filtered, as taught by Theverapperuma, in order to improve the accuracy and quality of terrain and obstacle data obtained by the one or more optical sensor (Theverapperuma, Para. 0091).
In regards to Claim 2, Ready in view of Theverapperuma teaches the method of Claim 1, and Ready further teaches calculating an estimated elevation of the cutting edge of the attachment relative to a ground surface using the calculated position of the cutting edge and comparing the estimated elevation with a target grade to determine a deviation (Ready, Para. 0088-0094 – while “moving through the earth moving routine at the dig location, the earth moving engine 430 tracks 658 the position and orientation of the earth moving tool 175 within the coordinate system” and determining a “deviation between the target tool path and the actual tool path”; where the tool path includes a “depth below the ground surface at which the earth moving tool 175 is placed”, i.e. “defining the height at which the leading edge is lowered”),
wherein autonomously controlling the asset to adjust the position and the orientation of the attachment to maintain the calculated position of the cutting edge at the target grade is performed using the deviation (Ready, Para. 0063, 0091, 0108 – “a target tool path may include instructions to adjust a position and an orientation of an earth moving tool 175 before, after, or during the performance of an earth moving operation or earth moving routine”, repeating “the same target tool path until a deviation between the target tool path and the actual tool path is less than a threshold deviation”, or further, “if the difference in the set of coordinates for the actual tool path and the target tool path is greater than a threshold difference, the distribution of hydraulic pressure is adjusted to lower or raise the earth moving tool 175 at a greater or lesser depth below the ground surface to more closely match the target tool path”).
In regards to Claim 3, Ready in view of Theverapperuma teaches the method of Claim 1, and Ready further teaches further comprising: receiving an excavation location and a pile location (Ready, Para. 0056-0057 – a “navigation engine 410” which provides locations in the dig site, such as “a location of earth to be moved”, or excavation location, and “a location at which earth is to be filled”, or pile location), wherein the movement of the asset is autonomously controlled between the excavation location and the pile location (Ready, Para. 0023, 0028, 0057, 0063, 0068-0069 – “an earth moving system 100 for moving… earth autonomously or semi-autonomously from a dig site”, such as “routines for excavating earth from a location in the dig site, hauling earth from one location to another in the dig site, filling or depositing earth excavated from one location at another”, etc.) and the point cloud data that is filtered is processed to identify the terrain features and the obstacles while the asset is moving between the excavation location and the pile location (Ready, Para. 0045, 0067, 0092 – as a “navigation engine 410 maneuvers the earth moving vehicle 115 through the dig site, sensors 170 gather contextual information on the dig site which is aggregated into a representation of the current state of the dig site”; where the sensor data is processed, including “filtering”, to obtain “a real-time scan of the ground surface of the dig site around the earth moving vehicle”, and identify “one or more obstacles”).
In regards to Claim 4, Ready in view of Theverapperuma teaches the method of Claim 3, and Ready further teaches wherein the movement of the asset is autonomously controlled between the excavation location and the pile location without a previously defined path being received, calculated, or obtained (Ready, Para. 0069-0071, 0093, 0108 – where the earth moving vehicle may identify “an obstruction, for example an obstacle or another earth moving vehicle 115… to be within the target tool path” at a “current location” of the earth moving vehicle, and perform a different routine instead, such as “a break routine to hopefully break up and/or remove the object”, such that the path is defined in the moment, where further, it may be determined that a “difference in the set of coordinates for the actual tool path and the target tool path is greater than a threshold difference” and the earth moving tool position may be adjusted; where the “target tool path” is determined based on “a digital terrain model of the dig site” generated from “a current physical state of the dig site generated based on the sensor data”).
In regards to Claim 5, Ready in view of Theverapperuma teaches the method of Claim 1, and Ready in view of Theverapperuma further teaches wherein filtering the point cloud data includes removing data points associated with a reflectivity value that is below a predetermined threshold (Theverapperuma, Para. 0091-0092 – “conditioning operations include operations to eliminate noise or unneeded information” such as “eliminating LIDAR data captured outside of a certain field of view, removing data corresponding to objects or regions that are not of interest (e.g., the ground), etc.)” and “adjusting a reflectivity parameter to change the operating range of the LIDAR/radar sensor (e.g., to prevent capturing of data beyond a certain distance when an object of interest, such as pile, is known to be less than that distance away from the vehicle)”, such that low reflectivity values are preemptively removed) and applying one or more than one box filter to isolate the data points associated with the terrain features from the data points associated with the asset (Theverapperuma, Para. 0007, 0013, 0091-0092 0156 – “detection of an object” may include “determining that adjacent or nearby regions of the same class belong to the same object” and generating “an output representation indicating boundaries between, for example, a pile object and a non-pile object”; where a “3D representation of the pile of material” is generated using a “Bayesian filter”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of including the above limitations of Ready in view of Theverapperuma to further include wherein filtering the point cloud data includes removing data points associated with a reflectivity value that is below a predetermined threshold and applying one or more than one box filter to isolate the data points associated with the terrain features from the data points associated with the asset, as taught by Theverapperuma, in order to improve the accuracy of terrain and obstacle detection (Theverapperuma, Para. 0091, 0145).
In regards to Claim 6, Ready in view of Theverapperuma teaches the method of Claim 1, and Ready further teaches further comprising: generating a terrain map of an area surrounding the asset using the point cloud data that is filtered, the position data, and the movement data that is fused (Ready, Para. 0045, 0067-0069 – “the on-unit computer 120a may fuse data from the various sensors” comprising “fusing the point clouds from various spatial sensors 130, the stitching of images from multiple imaging sensors 135, and registration of images and point clouds relative to each other or relative to data regarding an external reference frame as provided by position sensors 145”, and generating “a representation of the initial state of the dig site using sensor 170 data”, where “spatial sensors 130 record spatial data in the form of point cloud representations, imaging sensors 135 gather imaging data, and depth sensors 145 gather data describing relative locations”).
Regarding Claim 9, Ready teaches: A machine guidance system (Ready, Para. 0001-0004 – “an autonomous or semi-autonomous earth moving system” for “autonomously executing earth moving operations by an earth moving vehicle”) comprising:
one or more than one optical sensor mounted on an asset (Ready, Para. 0025, 0030, 0033 – an “earth moving system”, or asset, including “a sensor assembly 110” which includes “spatial sensors 130”, such as “a LIDAR sensor”), the one or more than one optical sensor sensing an area around the asset and outputting point cloud data representative of portions of terrain and obstacles outside of the asset (Ready, Para. 0033 – the “LiDAR sensor” outputs “a three-dimensional point cloud representing distances between one meter and fifty meters between the spatial sensors 130 and the ground surface or any objects within the field of view of each spatial sensor 130”);
one or more than one position sensor mounted on the asset and configured to output position data indicative of geographic positions of the one or more than one position sensor (Ready, Para. 0025, 0032, 0084, 0090 – “sensor assembly 110” of the “earth moving system” includes “position sensors 145” which provide “a position of the earth moving vehicle 115” as “a localized position within a dig site, or a global position with respect latitude/longitude, or some other external reference system”);
a movement sensor mounted on the asset and configured to output movement data indicative of movement of the movement sensor (Ready, Para. 0025, 0032, 0035, 0120 – “sensor assembly 110” of the “earth moving system” includes “measurement sensors 125” such as “inertial measurement unit sensors” for determining “movement and position of the earth moving tool 175”); and
a processing unit configured to receive and filter the point cloud data that is received (Ready, Para. 0033, 0045, 0140 – an “on-unit computer 120a”, including “a computer processor”, may also process the data received from the sensor assembly 110” including “spatial sensors 130”, the processing including “filtering” and “smoothing”; where the spatial sensor data outputted is “a three-dimensional point cloud”)
the processing unit examining the point cloud data that is filtered to identify terrain features and obstacles (Ready, Para. 0033, 0045 – “on-unit computer 120a may also process the data received from the sensor assembly 110” including “spatial sensors 130” to obtain “a real-time scan of the ground surface of the dig site around the earth moving vehicle”, the processing comprising “fusing the point clouds from various spatial sensors 130”, the point clouds representing “distances between one meter and fifty meters between the spatial sensors 130 and the ground surface or any objects within the field of view of each spatial sensor 130”) and
autonomously controlling movement of the asset and an attachment to the asset using the terrain features and the obstacles that are identified (Ready, Para. 0023, 0028, 0057, 0068-0069 – “an earth moving system 100 for moving… earth autonomously or semi-autonomously from a dig site”, the earth moving system including an “earth moving tool 175”, or attachment; where the earth moving system “executes instructions (e.g., instructions encoded as a set of target tool paths) to actuate one or more tools 175 and the drive train to perform an earth moving routine, for example an earth moving routine to excavate earth from a location in a dig site, a filling routine to fill earth at a location in the dig site”, etc. based on “a digital terrain model of the dig site” obtained from “the sensor data” from “spatial sensors 130”),
the processing unit configured to fuse the point cloud data that is filtered, the position data, and the movement data to calculate a real-world position, orientation, and a calculated position of a cutting edge of an attachment to the asset (Ready, Para. 0045, 0068-0072, 0088-0090 – “on-unit computer 120a may fuse data from the various sensors” comprising “fusing the point clouds from various spatial sensors 130, the stitching of images from multiple imaging sensors 135, and registration of images and point clouds relative to each other or relative to data regarding an external reference frame as provided by position sensors 145”; where the “position and orientation of the earth moving tool 175”, including “the leading edge of the earth moving tool”, is determined “relative to a reference orientation” such as “the ground surface , a gravity vector, or a target tool path” generated based on the “digital terrain model of the dig site” generated from data provided by “spatial sensors 130”),
the processing unit configured to autonomously control the asset to adjust the position and the orientation of the attachment to maintain the calculated position of a cutting edge of the attachment at a target grade during at least some of the movement of the asset that is autonomously controlled (Ready, Para. 0043, 0063, 0088-0090, 0121 – “earth moving engine 430 receives 650 the one or more target tool paths generated by the preparation engine 420 and positions 652 the leading edge of the earth moving tool 175 below the ground surface… guided by the operations outlined in a target tool path”, the “target tool path... includes instructions to actuate an excavation tool beneath a ground surface and to maintain the position of the earth moving tool 175” and to “adjust an orientation of a earth moving tool 175 to effectively penetrate the ground surface”; where the “earth moving vehicle 115 is designed to carry out the set of instructions of an earth moving routine either entirely autonomously or semi-autonomously”).
Ready does not fully teach filter the point cloud data that is received based on one or more predetermined thresholds and by applying one or more spatial filters to isolate features of the terrain from the point cloud data that is filtered.
However, Theverapperuma teaches filter the point cloud data that is received based on one or more predetermined thresholds and by applying one or more spatial filters to isolate features of the terrain from the point cloud data that is filtered (Theverapperuma, Para. 0012-0013, 0090-0095, 0113 – obtaining “a point cloud generated using a LIDAR or radar sensor”, using “a machine learning model that has been trained to detect pile shapes from point clouds”, and “generating the 3D representation of the pile of material”; where conditioning operations are applied to sensor data, including “operations to eliminate noise or unneeded information (e.g., cropping of images, eliminating LIDAR data captured outside of a certain field of view, removing data corresponding to objects or regions that are not of interest… etc.)”, i.e. eliminating data outside a threshold range, and identifying “instances” of objects, for example “pile #1, pile #2”, such that the features are isolated).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the machine guidance system of Ready to include filter the point cloud data that is received based on one or more predetermined thresholds and by applying one or more spatial filters to isolate features of the terrain from the point cloud data that is filtered, as taught by Theverapperuma, in order to improve the accuracy of terrain and obstacle data obtained by the one or more optical sensor (Theverapperuma, Para. 0091).
In regards to Claim 10, Ready in view of Theverapperuma teaches the machine guidance system of Claim 9, and Ready further teaches wherein the processing unit is configured to calculate an estimated elevation of the cutting edge of the attachment relative to a ground surface using the calculated position of the cutting edge and comparing the estimated elevation with a target grade to determine a deviation (Ready, Para. 0088-0094 – while “moving through the earth moving routine at the dig location, the earth moving engine 430 tracks 658 the position and orientation of the earth moving tool 175 within the coordinate system” and determining a “deviation between the target tool path and the actual tool path”; where the tool path includes a “depth below the ground surface at which the earth moving tool 175 is placed”, i.e. “defining the height at which the leading edge is lowered”),
wherein the processing unit is configured to autonomously control the asset to adjust the position and the orientation of the attachment to maintain the calculated position of the cutting edge at the target grade using the deviation (Ready, Para. 0063, 0091, 0108 – “a target tool path may include instructions to adjust a position and an orientation of an earth moving tool 175 before, after, or during the performance of an earth moving operation or earth moving routine”, repeating “the same target tool path until a deviation between the target tool path and the actual tool path is less than a threshold deviation”, or further, “if the difference in the set of coordinates for the actual tool path and the target tool path is greater than a threshold difference, the distribution of hydraulic pressure is adjusted to lower or raise the earth moving tool 175 at a greater or lesser depth below the ground surface to more closely match the target tool path”).
In regards to Claim 11, Ready in view of Theverapperuma teaches the machine guidance system of Claim 9, and Ready further teaches wherein the processing unit is configured to receive an excavation location and a pile location (Ready, Para. 0056-0057 – a “navigation engine 410” which provides locations in the dig site, such as “a location of earth to be moved”, or excavation location, and “a location at which earth is to be filled”, or pile location), and the processing unit is configured to autonomously control the movement of the asset between the excavation location and the pile location (Ready, Para. 0023, 0028, 0057, 0063, 0068-0069 – “an earth moving system 100 for moving… earth autonomously or semi-autonomously from a dig site”, such as “routines for excavating earth from a location in the dig site, hauling earth from one location to another in the dig site, filling or depositing earth excavated from one location at another”, etc.) and the processing unit is configured to identify the terrain features and the obstacles from the point cloud data that is filtered while the asset is moving between the excavation location and the pile location (Ready, Para. 0045, 0067, 0092 – as a “navigation engine 410 maneuvers the earth moving vehicle 115 through the dig site, sensors 170 gather contextual information on the dig site which is aggregated into a representation of the current state of the dig site”; where the sensor data is processed, including “filtering”, to obtain “a real-time scan of the ground surface of the dig site around the earth moving vehicle”, and identify “one or more obstacles”).
In regards to Claim 12, Ready in view of Theverapperuma teaches the machine guidance system of Claim 11, and Ready further teaches wherein the processing unit autonomously controls the movement of the asset between the excavation location and the pile location without a previously defined path being received, calculated, or obtained (Ready, Para. 0069-0071, 0093, 0108 – where the earth moving vehicle may identify “an obstruction, for example an obstacle or another earth moving vehicle 115… to be within the target tool path” at a “current location” of the earth moving vehicle, and perform a different routine instead, such as “a break routine to hopefully break up and/or remove the object”, such that the path is defined in the moment, where further, it may be determined that a “difference in the set of coordinates for the actual tool path and the target tool path is greater than a threshold difference” and the earth moving tool position may be adjusted; where the “target tool path” is determined based on “a digital terrain model of the dig site” generated from “a current physical state of the dig site generated based on the sensor data”).
In regards to Claim 13, Ready in view of Theverapperuma teaches the machine guidance system of Claim 9, and Ready in view of Theverapperuma further teaches wherein the processing unit is configured to filter the point cloud data by removing data points associated with a reflectivity value that is below a predetermined threshold (Theverapperuma, Para. 0091-0092 – “conditioning operations include operations to eliminate noise or unneeded information” such as “eliminating LIDAR data captured outside of a certain field of view, removing data corresponding to objects or regions that are not of interest (e.g., the ground), etc.)” and “adjusting a reflectivity parameter to change the operating range of the LIDAR/radar sensor (e.g., to prevent capturing of data beyond a certain distance when an object of interest, such as pile, is known to be less than that distance away from the vehicle)”, such that low reflectivity values are preemptively removed) and by applying one or more than one box filter to isolate the data points associated with the terrain features from the data points associated with the asset (Theverapperuma, Para. 0007, 0013, 0091-0092 0156 – “detection of an object” may include “determining that adjacent or nearby regions of the same class belong to the same object” and generating “an output representation indicating boundaries between, for example, a pile object and a non-pile object”; where a “3D representation of the pile of material” is generated using a “Bayesian filter”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the machine guidance system of including the above limitations of Ready in view of Theverapperuma to further include wherein the processing unit is configured to filter the point cloud data by removing data points associated with a reflectivity value that is below a predetermined threshold and by applying one or more than one box filter to isolate the data points associated with the terrain features from the data points associated with the asset, as taught by Theverapperuma, in order to improve the accuracy of terrain and obstacle detection (Theverapperuma, Para. 0091, 0145).
In regards to Claim 14, Ready in view of Theverapperuma teaches the machine guidance system of Claim 9, and Ready further teaches wherein the processing unit is configured to generate a terrain map of an area surrounding the asset using the point cloud data that is filtered, the position data, and the movement data that is fused (Ready, Para. 0045, 0067-0069 – “the on-unit computer 120a may fuse data from the various sensors” comprising “fusing the point clouds from various spatial sensors 130, the stitching of images from multiple imaging sensors 135, and registration of images and point clouds relative to each other or relative to data regarding an external reference frame as provided by position sensors 145”, and generating “a representation of the initial state of the dig site using sensor 170 data”, where “spatial sensors 130 record spatial data in the form of point cloud representations, imaging sensors 135 gather imaging data, and depth sensors 145 gather data describing relative locations”).
Claim(s) 7-8 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Ready in view of Theverapperuma, and further in view of Foster, et al. (U.S. Patent Application Pub. No. 2017/0357267).
In regards to Claim 7, Ready in view of Theverapperuma teaches the method of Claim 6, but Ready in view of Theverapperuma does not teach wherein generating the terrain map comprises dividing the area surrounding the construction asset into a grid of cells, and for each of the cells, calculating an elevation value based on elevations of data points in the point cloud data that are projected into that cell.
However, Foster teaches wherein generating the terrain map comprises dividing the area surrounding the construction asset into a grid of cells (Foster, Para. 0004 – “create or update a map of one or more cells that correspond to one or more locations of the work area, wherein each of the one or more cells indicate whether the obstacle occupies the respective locations of the work area based on the points of the point cloud”), and for each of the cells, calculating an elevation value based on elevations of data points in the point cloud data that are projected into that cell (Forster, Para. 0033 – “the processor 50 may determine that an obstacle is occupying the location that corresponds to the grid cell… by calculation of a gradient (e.g., slopes) between the points of the point cloud”, where “each grid cell may be independent of one another”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the method including the above limitations of Ready in view of Theverapperuma to further include wherein generating the terrain map comprises dividing the area surrounding the construction asset into a grid of cells, and for each of the cells, calculating an elevation value based on elevations of data points in the point cloud data that are projected into that cell, as taught by Foster, in order to improve the accuracy of obstacle detection.
In regards to Claim 8, Ready in view of Theverapperuma and Foster teaches the method of Claim 7, and Ready in view of Theverapperuma and Foster further teaches further comprising: updating only the cells in the grid of the terrain map that correspond to locations with newly received or modified point cloud data (Foster, Para. 0004, 0032-0035 – “update a map of one or more cells that correspond to one or more locations of the work area”, where “each grid cell may be independent of one another and have a prior probability indicating a probability that the respective grid cell had an obstacle”, where updating includes determining “that an obstacle is occupying the location that corresponds to the grid cell” and indicating “the cell as an obstacle” if “the probability of an obstacle is greater than a threshold probability”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method including the above limitations of Ready in view of Theverapperuma and Foster to further include further comprising: updating only the cells in the grid of the terrain map that correspond to locations with newly received or modified point cloud data, as taught by Foster, in order to provide accurate and updated point cloud data.
In regards to Claim 15, Ready in view of Theverapperuma teaches the machine guidance system of Claim 14, but Ready in view of Theverapperuma does not teach wherein the processing unit is configured to generate the terrain map by dividing the area surrounding the construction asset into a grid of cells, and for each of the cells, calculating an elevation value based on elevations of data points in the point cloud data that are projected into that cell.
However, Foster teaches wherein the processing unit is configured to generate the terrain map by dividing the area surrounding the construction asset into a grid of cells (Foster, Para. 0004 – “create or update a map of one or more cells that correspond to one or more locations of the work area, wherein each of the one or more cells indicate whether the obstacle occupies the respective locations of the work area based on the points of the point cloud”), and for each of the cells, calculating an elevation value based on elevations of data points in the point cloud data that are projected into that cell (Forster, Para. 0033 – “the processor 50 may determine that an obstacle is occupying the location that corresponds to the grid cell… by calculation of a gradient (e.g., slopes) between the points of the point cloud”, where “each grid cell may be independent of one another”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the machine guidance system including the above limitations of Ready in view of Theverapperuma to further include wherein the processing unit is configured to generate the terrain map by dividing the area surrounding the construction asset into a grid of cells, and for each of the cells, calculating an elevation value based on elevations of data points in the point cloud data that are projected into that cell, as taught by Foster, in order to improve the accuracy of obstacle detection.
In regards to Claim 16, Ready in view of Theverapperuma and Foster teaches the machine guidance system of Claim 15, and Ready in view of Theverapperuma and Foster further teaches wherein the processing unit updates only the cells in the grid of the terrain map that correspond to locations with newly received or modified point cloud data (Foster, Para. 0004, 0032-0035 – “update a map of one or more cells that correspond to one or more locations of the work area”, where “each grid cell may be independent of one another and have a prior probability indicating a probability that the respective grid cell had an obstacle”, where updating includes determining “that an obstacle is occupying the location that corresponds to the grid cell” and indicating “the cell as an obstacle” if “the probability of an obstacle is greater than a threshold probability”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the machine guidance system including the above limitations of Ready in view of Theverapperuma and Foster to further include wherein the processing unit updates only the cells in the grid of the terrain map that correspond to locations with newly received or modified point cloud data, as taught by Foster, in order to provide accurate and updated point cloud data.
Claim(s) 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ready in view of Thibblin, et al. (U.S. Patent Application Pub. No. 2021/0254308).
In regards to Claim 18, Ready teaches the method of Claim 17, but Ready does not teach wherein the point cloud data is obtained by the LiDAR sensors measuring reflection off reflective surfaces on the asset and the attachment.
However, Thibblin teaches wherein the point cloud data is obtained by the LiDAR sensors measuring reflection off reflective surfaces on the asset and the attachment (Thibblin, Fig. 9 and 10, Para. 0017, 0045, 0051-0055, 0068 – a “3D point cloud… collected with the LiDAR scanner” by determining “a distance value based on the speed of light and a measured time between sending out the respective pulse and receiving its reflection pulse”; where “LiDAR scanners… keep track of the pose of the target(s)” and are “configured to track a pose of a target mounted to an earth-moving tool of the construction machine”, the “target 81/91”, mounted on exemplary tools as shown in Fig. 9 and 10, having “a predetermined referenced location and alignment on the tool”).
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Thibblin, Fig. 9 and 10
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Ready to include wherein the point cloud data is obtained by the LiDAR sensors measuring reflection off reflective surfaces on the asset and the attachment, as taught by Thibblin, in order to provide quicker and more accurate detection and improve autonomous drive capability (Thibblin, Para. 0008).
In regards to Claim 19, Ready teaches the method of Claim 17, but Ready does not teach wherein the point cloud data is processed to identify the terrain features and the obstacles by applying one or more than one box filter associated with the asset and with the attachment to the point cloud data.
However, Thibblin teaches wherein the point cloud data is processed to identify the terrain features and the obstacles by applying one or more than one box filter associated with the asset and with the attachment to the point cloud data (Thibblin, Para. 0045, 0049, 0051-0055, 0061, 0068-0072 – a “3D point cloud… collected with the LiDAR scanner” used by a computer for “recognizing objects” and “three-dimensional camera target[s]” by detecting “a specific wavelength range” and fusing sensor data processed by “a Kalman filter”; where “LiDAR scanners… keep track of the pose of the target(s)”, which are “mounted to an earth-moving tool of the construction machine”, and identify “an obstacle or a person within the first detection range”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Ready to include wherein the point cloud data is processed to identify the terrain features and the obstacles by applying one or more than one box filter associated with the asset and with the attachment to the point cloud data, as taught by Thibblin, in order to provide quicker and more accurate detection and improve autonomous drive capability (Thibblin, Para. 0008).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Takahama, et al. (U.S. Patent Application Pub. No. 2021/0238828) teaches a display control device and a display control method for displaying where at least the work equipment appears in the captured image, further including a map generation unit which generates a three-dimensional map representing the surrounding shape of the work machine.
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/H.L./Examiner, Art Unit 3665
/HUNTER B LONSBERRY/Supervisory Patent Examiner, Art Unit 3665
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