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 .
Response to Amendment
This communication is in response to the action filed on 01/30/2026.
The claims 8-9, 15, and 20 are currently amended. The claims 1-20 are pending.
Response to Arguments
Applicant’s arguments filed on 01/30/2026 on pages 8-13, under REMARKS with respect to 35 U.S.C. 103 claim rejections to claims 1-20 have been fully considered and are persuasive. The rejections to the claims have been withdrawn. However, upon further consideration, a new ground of rejection is made in view of US 2018/0341021 A1.
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.
(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.
Claims 1, 8, and 15 are rejected under 35 § U.S.C. 102(a)(1) as being anticipated by US 2018/0341021 A1 to SCHMITT et al. (hereinafter “SCHMITT”).
As per claim 1, SCHMITT discloses a method, comprising: deriving, by one or more computing devices (a computing system and corresponding method of operation in order to derive object position using an on board computing system connected to a lidar sensor of a vehicle; abstract; fig 1; paragraphs [0003-0006], [0009-0016]), a query point cloud from a sweep of a light detection and ranging “lidar” sensor device of a vehicle and a reference point cloud from a high- definition “HD” map (a vehicle such as a car or space craft equipped with an on board computing system connected to a LIDAR sensor which uses a laser (sweep of light) to measure a target object distance from said vehicle and uses a point cloud reflection method in combination with position algorithms in order to estimate relative object position using reference/scanning point clouds; fig 1; paragraphs [0002-0006], [0009-0016]); extracting, by the one or more computing devices, a first set of features from the query point cloud and a second set of features from the reference point cloud (the position of the target object can be determined (extracted) using the Iterative Closest Point Algorithms which adapt a mathematical reference model (which would include the first and second sets of features) to the 3D point cloud, acquired by the LIDAR sensor in the course of continuously performed scans, by means of an iterative adaptation method; fig 1; paragraphs [0009-0016], [0019]); determining, by the one or more computing devices, a coarse alignment by generating a plurality of transformation solutions through graduated non-convexity “GNC” optimization with a plurality of uniformly sampled initial vehicle headings (the system is adapted to determine guidance, navigation, and control of the vehicle (course alignment) using a GNC system, a LIDAR sensor and a point cloud to position a satellite vehicle but is stated the tech would translate to a car vehicle, it does this by iteratively (uniformly sampled) applying point clouds to determine object position and location (vehicle headings) as it moves through the scanned point clouds and adapts a reference model which is continually improved (optimized); fig 1; paragraphs [0003-0006], [0009-0016], [0019]), wherein the generating is based on a plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud (using the reflected points (matches) of the point clouds used to scan for objects the reflected points are used to determine a reference object and location/position the model uses those reflected points to determine a mathematical reference model using iterative closest point algorithms to estimate position a common practice in the art; fig 1; paragraphs [0003-0006], [0009-0016], [0019]); and estimating, by the one or more computing devices, a position-orientation pose of the vehicle by refining the coarse alignment using an iterative closest point “ICP” algorithm (the target object position is estimated by the mathematical reference model using iterative closest point position estimation algorithms and the model is constantly improved using point cloud scans; fig 1; paragraphs [0003-0006], [0009-0016], [0019]).
As per claim 8, SCHMITT discloses a non-transitory computer-readable medium storing instructions that, when executed by one or more processors (a system and method for spacecraft/vehicle navigation which would include a computer which would include a memory component to store instructions when executed by the computer processor would perform a method of operation; paragraphs [0003], [0016], [0019]), causes the one or more processors to perform operations comprising: deriving a query point cloud from a sweep of a light detection and ranging (lidar) sensor device of a vehicle and a reference point cloud from a high-definition (HD) map (said method of operation causes a vehicle such as a car or space craft equipped with an on board computing system connected to a LIDAR sensor which uses a laser (sweep of light) to measure a target object distance from said vehicle and uses a point cloud reflection method in combination with position algorithms in order to estimate relative object position using reference/scanning point clouds to for a high definition 3D model; fig 1; paragraphs [0002-0006], [0009-0016]); extracting a first set of features from the query point cloud and a second set of features from the reference point cloud (the position of the target object can be determined (extracted) using the Iterative Closest Point Algorithms which adapt a mathematical reference model (which would include the first and second sets of features) to the 3D point cloud, acquired by the LIDAR sensor in the course of continuously performed scans, by means of an iterative adaptation method; fig 1; paragraphs [0009-0016], [0019]); determining a coarse alignment by generating a plurality of transformation solutions through graduated non-convexity (GNC) optimization with a plurality of uniformly sampled initial vehicle headings (the system is adapted to determine guidance, navigation, and control of the vehicle (course alignment) using a GNC system, a LIDAR sensor and a point cloud to position a satellite vehicle but is stated the tech would translate to a car vehicle, it does this by iteratively (uniformly sampled) applying point clouds to determine object position and location (vehicle headings) as it moves through the scanned point clouds and adapts a reference model which is continually improved (optimized); fig 1; paragraphs [0003-0006], [0009-0016], [0019]), wherein the generating is based on a plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud (using the reflected points (matches) of the point clouds used to scan for objects the reflected points are used to determine a reference object and location/position the model uses those reflected points to determine a mathematical reference model using iterative closest point algorithms to estimate position a common practice in the art; fig 1; paragraphs [0003-0006], [0009-0016], [0019]); and estimating a position-orientation pose of the vehicle by refining the coarse alignment using an iterative closest point (ICP) algorithm (the target object position is estimated by the mathematical reference model using iterative closest point position estimation algorithms and the model is constantly improved using point cloud scans; fig 1; paragraphs [0003-0006], [0009-0016], [0019]).
As per claim 15, SCHMITT discloses a system, comprising: one or more processors (a system and method for spacecraft/vehicle navigation which would include a computer which would include a memory component to store instructions when executed by the computer processor would perform a method of operation; paragraphs [0003], [0016], [0019]); and a memory communicatively coupled to the one or more processors, wherein the memory stores instructions that, when executed by the one or more processors (a system and method for spacecraft/vehicle navigation which would include a computer which would include a memory component to store instructions when executed by the computer processor would perform a method of operation; paragraphs [0003], [0016], [0019]), cause the one or more processors to perform operations comprising: deriving a query point cloud from a sweep of a light detection and ranging (lidar) sensor device of a vehicle and a reference point cloud from a high-definition (HD) map (said method of operation causes a vehicle such as a car or space craft equipped with an on board computing system connected to a LIDAR sensor which uses a laser (sweep of light) to measure a target object distance from said vehicle and uses a point cloud reflection method in combination with position algorithms in order to estimate relative object position using reference/scanning point clouds to for a high definition 3D model; fig 1; paragraphs [0002-0006], [0009-0016]); extracting a first set of features from the query point cloud and a second set of features from the reference point cloud determining a coarse alignment based on a plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud (the position of the target object can be determined (extracted) using the Iterative Closest Point Algorithms which adapt a mathematical reference model (which would include the first and second sets of features) to the 3D point cloud, acquired by the LIDAR sensor in the course of continuously performed scans, by means of an iterative adaptation method; fig 1; paragraphs [0009-0016], [0019]); and estimating a position-orientation pose of the vehicle by refining the coarse alignment using an iterative closest point (ICP) algorithm (using the reflected points (matches) of the point clouds used to scan for objects the reflected points are used to determine a reference object and location/position the model uses those reflected points to determine a mathematical reference model using iterative closest point algorithms to estimate position of the detected object, and refines/ improves the model continuously to estimate object position in relation to the vehicle; fig 1; paragraphs [0003-0006], [0009-0016], [0019]), wherein the determining the coarse alignment further comprises: generating a plurality of solutions by applying a predetermined number of distinct graduated non-convexity (GNC) optimizations with uniformly sampled initial vehicle headings to the plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud (the system is adapted to determine guidance, navigation, and control of the vehicle (course alignment) using a GNC system, a LIDAR sensor and a point cloud to position a satellite vehicle but is stated the tech would translate to a car vehicle, it does this by iteratively (uniformly sampled) applying point clouds to determine object position and location (vehicle headings) as it moves through the scanned point clouds and adapts a reference model which is continually improved (optimized); fig 1; paragraphs [0003-0006], [0009-0016], [0019]).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 2-3, 5-7, 9-10, 12-14, 16-17, and 19-20 are rejected under 35 § U.S.C. 103 as being obvious over US 2018/0341021 A1 to SCHMITT et al. (hereinafter “SCHMITT”) in view of WO 2020/139377 A1 to ZHANG et al. (hereinafter “ZHANG”).
As per claim 2, SCHMITT discloses the method of claim 1. SCHMITT fails to disclose wherein the deriving the reference point cloud from the HD map further comprises: selecting, by the one or more computing devices and based on geolocation data obtained from one or more geolocation sensor devices of the vehicle at commencement of an activation sequence of the vehicle, a map tile comprising a predefined geographical area that includes an initial location of the vehicle from a plurality of map tiles in the HD map; and obtaining, by the one or more computing devices, the reference point cloud from the selected map tile in the HD map.
ZHANG discloses wherein the deriving the reference point cloud from the HD map further comprises: selecting, by the one or more computing devices and based on geolocation data obtained from one or more geolocation sensor devices of the vehicle at commencement of an activation sequence of the vehicle (the computing system is adapted to provide geographic location data related to sensors resident on the vehicle various radar sensors and allow for real time position /location data relating to the vehicle in relation to the generated map and travel path; paragraphs [0028], [0032], [0082], [0091]; Claim 15), a map tile comprising a predefined geographical area that includes an initial location of the vehicle from a plurality of map tiles in the HD map (the computing system is adapted to provide geographic location data related to map data 154 which allows for generation of a 3D map which depicts and shows various street elements including layout of streets, buildings, road details and information, land marks, intersections, bridges, and various other map points of interest; paragraphs [0028], [0082], [0091]; Claim 15); and obtaining, by the one or more computing devices, the reference point cloud from the selected map tile in the HD map (the computing device in communication with server 130 can transmit the map data 154 to a vehicle 120 for storage therein in the on vehicle data store 129; paragraphs [0032-0033], [0056-0061]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have a map tile comprising a predefined geographical area of ZHANG reference. The Suggestion/motivation for doing so would have been to provide various user interface tools and associated computer functionality that enables integrated visual exploration and editing with respect to both two-dimensional (2D) and three-dimensional (3D) visualizations of captured LiDAR data, pose graphs, and map data in order to build more accurate HD maps according to paragraph [0015] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 2.
As per claim 3, SCHMITT discloses the method of claim 1. SCHMITT fails to disclose further comprising: down sampling, by the one or more computing devices, voxels in the query point cloud and the reference point cloud; and deriving, by the one or more computing devices, a surface normal for each of the query point cloud and the reference point cloud.
ZHANG discloses further comprising: down sampling, by the one or more computing devices, voxels in the query point cloud and the reference point cloud (the computing system provides a user interface via which the user may down scale/ zoom in a 2D map projection of a 3D point cloud rendering if the zoom scale meets a predefined threshold; paragraphs [0072], [0082-0084]; figures 4 and 8); and deriving, by the one or more computing devices, a surface normal for each of the query point cloud and the reference point cloud (data processing system 123 provides processed data 162 to the vehicle control system 126 to respond to point-to-point activity in the surroundings of the vehicle 120, processed data 162 is comparisons between the raw sensor data 161 representing an operational environment of the vehicle 120, which is continuously monitored via sensor array 121-and the map data stored in the data store 129, further the data processing system 123 is programmed with machine learning or other artificial intelligence capabilities to enable the vehicle 120 to identify and respond to conditions, events, and/or potential hazards on a surface such as a road while driving in traffic using the road as the normal surface to measure the point clouds and corresponding objects which reflect points back; paragraphs [0052]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have down sampling, by the one or more computing devices, voxels in the query point cloud and the reference point cloud of ZHANG reference. The Suggestion/motivation for doing so would have been to provide on board localization of the vehicle in the environment allowing vehicle to become aware of an instant location and orientation of the vehicle in comparison to the stored map data in order to maneuver the vehicle on surface streets through traffic and assist a driver in maneuvering the vehicle on surface streets through traffic and identify and respond to potential hazards or local conditions, such as weather or traffic conditions as suggested at paragraph [0052] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 3.
As per claim 5, SCHMITT discloses the method of claim 1. SCHMITT fails to disclose further comprising: generating, by the one or more computing devices, the plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud by pairing each point in the query point cloud with a closest neighboring point in the reference point cloud.
ZHANG discloses further comprising: generating, by the one or more computing devices, the plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud by pairing each point in the query point cloud with a closest neighboring point in the reference point cloud (the computing system is adapted to provide over said user interfaces for viewing HD maps at different levels, exploring 3D point clouds of a certain part of an HD map, measuring the distance between two points from maps or point clouds from related positions, and tuning parts of a map to better align or match (pair) two or more point clouds; figs 3-4; paragraphs [0056-0058], [0069-0072]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have pairing each point in the query point cloud with a closest neighboring point in the reference point cloud of ZHANG reference. The Suggestion/motivation for doing so would have been to provide positioning algorithms such as an iterative closest point ICP algorithm to perform the dimensional analysis steps in order to allow for higher accuracy in the map models which are developed and will allow the user to in the user interface 300 enable scrolling, panning, rotating, selecting, and zooming in either view provided as suggested by paragraphs [0069-0071 of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 5.
As per claim 6, SCHMITT discloses the method of claim 1. SCHMITT fails to disclose wherein the determining the coarse alignment further comprises: determining, by the one or more computing devices, a number of inlier feature matches for each transformation solution in the plurality of transformation solutions; and identifying, by the one or more computing devices, the transformation solution with the highest number of inlier feature matches as the coarse alignment.
ZHANG discloses wherein the determining the coarse alignment further comprises: determining, by the one or more computing devices, a number of inlier feature matches for each transformation solution in the plurality of transformation solutions (the computing devices are adapted to further provide options, via the user interface, to select a command and an associated scale for the command, wherein the scale represents a numeric amount of at least one of: movement, yaw, pitch or roll and further the suggested commands can include movement along each of an x axis, y axis and z axis; paragraphs [0096-0099], [0102-0105]); and identifying, by the one or more computing devices, the transformation solution with the highest number of inlier feature matches as the coarse alignment (the user interface operations comprise automatically determining a suggested spatial manipulation of the first set of point cloud data to better match at least the first subset of points with the second subset of points by automatically applying the suggested spatial manipulation within the 3D rendering displayed in the user interface, pending user approval of the suggested spatial manipulation the manipulation is determined based at least in part on a determination that the first set of point cloud data and the second set of point cloud data are misaligned by less than a threshold, wherein the threshold represents at least one of a distance or an angle feature; paragraphs [0096-0099], [0102-0105]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have identifying, by the one or more computing devices, the transformation solution with the highest number of inlier feature matches as the coarse alignment of ZHANG reference. The Suggestion/motivation for doing so would have been to provide the ability to edit the maps based on points feature matching by providing a method which further includes displaying, within the user interface, a plurality of suggested commands for altering positioning of the first set of point cloud data in 3D virtual space in order to better match at least the first subset of points with the second subset of points as suggested by paragraph [0099] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 6.
As per claim 7, SCHMITT in view of ZHANG discloses the method of claim 6. SCHMITT fails to disclose wherein each inlier feature match comprises a feature correspondence pair having a first point in the query point cloud and a second point in the reference point cloud that are within a predetermined distance threshold of each other.
ZHANG discloses wherein each inlier feature match comprises a feature correspondence pair having a first point in the query point cloud and a second point in the reference point cloud that are within a predetermined distance threshold of each other (the computing system is further adapted to provide the system may identify two or more point clouds that have edges that are misaligned by less than a threshold distance wherein the threshold is adjustable for example to, 0.1, 0.5, 1, etc. in the x axis, y axis, and/or z axis; paragraphs [0056-0058], [0085], [0103]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have wherein each inlier feature match comprises a feature correspondence pair having a first point in the query point cloud and a second point in the reference point cloud that are within a predetermined distance threshold of ZHANG reference. The Suggestion/motivation for doing so would have been to provide to the user the ability to perform spatial manipulation is determined based at least in part on a determination that the first set of point cloud data and the second set of point cloud data are misaligned by less than a threshold, wherein the threshold represents at least one of a distance or an angle as suggested by paragraph [00103] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 7.
As per claim 9, SCHMITT discloses the non-transitory computer-readable medium of claim 8. SCHMITT fails to disclose wherein the operations further comprise: selecting, based on geolocation data obtained from one or more geolocation sensor devices of the vehicle at commencement of an activation sequence of the vehicle, a map tile comprising a predefined geographical area that includes an initial location of the vehicle from a plurality of map tiles in the HD map; and obtaining the reference point cloud from the selected map tile in the HD map.
ZHANG discloses wherein the operations further comprise: selecting, based on geolocation data obtained from one or more geolocation sensor devices of the vehicle at commencement of an activation sequence of the vehicle (the computing system is adapted to provide geographic location data related to sensors resident on the vehicle various radar sensors and allow for real time position /location data relating to the vehicle in relation to the generated map and travel path; paragraphs [0028], [0032], [0082], [0091]; Claim 15), a map tile comprising a predefined geographical area that includes an initial location of the vehicle from a plurality of map tiles in the HD map (the computing system is adapted to provide geographic location data related to map data 154 which allows for generation of a 3D map which depicts and shows various street elements including layout of streets, buildings, road details and information, land marks, intersections, bridges, and various other map points of interest; paragraphs [0028], [0082], [0091]; Claim 15); and obtaining the reference point cloud from the selected map tile in the HD map (the computing device in communication with server 130 can transmit the map data 154 to a vehicle 120 for storage therein in the on vehicle data store 129; paragraphs [0032-0033], [0056-0061]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have a map tile comprising a predefined geographical area that includes an initial location of the vehicle from a plurality of map tiles in the HD map of ZHANG reference. The Suggestion/motivation for doing so would have been to provide various user interface tools and associated computer functionality that enables integrated visual exploration and editing with respect to both two-dimensional (2D) and three-dimensional (3D) visualizations of captured LiDAR data, pose graphs, and map data in order to build more accurate HD maps according to paragraph [0015] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 9.
As per claim 10, SCHMITT discloses the non-transitory computer-readable medium of claim 8. SCHMITT fails to disclose wherein the operations further comprise: down sampling voxels in the query point cloud and the reference point cloud; and deriving a surface normal for each of the query point cloud and the reference point cloud.
ZHANG discloses wherein the operations further comprise: down sampling voxels in the query point cloud and the reference point cloud (the computing system provides a user interface via which the user may down scale/ zoom in a 2D map projection of a 3D point cloud rendering if the zoom scale meets a predefined threshold; paragraphs [0072], [0082-0084]; figures 4 and 8); and deriving a surface normal for each of the query point cloud and the reference point cloud (data processing system 123 provides processed data 162 to the vehicle control system 126 to respond to point-to-point activity in the surroundings of the vehicle 120, processed data 162 is comparisons between the raw sensor data 161 representing an operational environment of the vehicle 120, which is continuously monitored via sensor array 121-and the map data stored in the data store 129, further the data processing system 123 is programmed with machine learning or other artificial intelligence capabilities to enable the vehicle 120 to identify and respond to conditions, events, and/or potential hazards on a surface such as a road while driving in traffic; paragraphs [0052]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have down sampling voxels in the query point cloud and the reference point cloud of ZHANG reference. The Suggestion/motivation for doing so would have been to provide on board localization of the vehicle in the environment allowing vehicle to become aware of an instant location and orientation of the vehicle in comparison to the stored map data in order to maneuver the vehicle on surface streets through traffic and assist a driver in maneuvering the vehicle on surface streets through traffic and identify and respond to potential hazards or local conditions, such as weather or traffic conditions as suggested at paragraph [0052] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 10.
As per claim 12, SCHMITT discloses the non-transitory computer-readable medium of claim 8. SCHMITT fails to disclose wherein the operations further comprise: generating the plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud by pairing each point in the query point cloud with a closest neighboring point in the reference point cloud.
ZHANG discloses wherein the operations further comprise: generating the plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud by pairing each point in the query point cloud with a closest neighboring point in the reference point cloud (the computing system is adapted to provide over said user interfaces for viewing HD maps at different levels, exploring 3D point clouds of a certain part of an HD map, measuring the distance between two points from maps or point clouds from related positions, and tuning parts of a map to better align or match (pair) two or more point clouds; paragraphs [0056-0058]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have generating the plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud by pairing each point in the query point cloud with a closest neighboring point in the reference point cloud of ZHANG reference. The Suggestion/motivation for doing so would have been to provide positioning algorithms such as an iterative closest point ICP algorithm to perform the dimensional analysis steps in order to allow for higher accuracy in the map models which are developed and will allow the user to in the user interface 300 enable scrolling, panning, rotating, selecting, and zooming in either view provided as suggested by paragraphs [0069-0071] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 12.
As per claim 13, SCHMITT discloses the non-transitory computer-readable medium of claim 8. SCHMITT fails to disclose wherein the determining the coarse alignment further comprises: determining a number of inlier feature matches for each transformation solution in the plurality of transformation solutions; and identifying the transformation solution with the highest number of inlier feature matches as the coarse alignment.
ZHANG discloses wherein the determining the coarse alignment further comprises: determining a number of inlier feature matches for each transformation solution in the plurality of transformation solutions (the computing devices are adapted to further provide options, via the user interface, to select a command and an associated scale for the command, wherein the scale represents a numeric amount of at least one of: movement, yaw, pitch or roll and further the suggested commands can include movement along each of an x axis, y axis and z axis; paragraphs [0102-0105]); and identifying the transformation solution with the highest number of inlier feature matches as the coarse alignment (the user interface operations comprise automatically determining a suggested spatial manipulation of the first set of point cloud data to better match at least the first subset of points with the second subset of points by automatically applying the suggested spatial manipulation within the 3D rendering displayed in the user interface, pending user approval of the suggested spatial manipulation the manipulation is determined based at least in part on a determination that the first set of point cloud data and the second set of point cloud data are misaligned by less than a threshold, wherein the threshold represents at least one of a distance or an angle feature; paragraphs [0102-0105]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have identifying the transformation solution with the highest number of inlier feature matches as the coarse alignment of ZHANG reference. The Suggestion/motivation for doing so would have been to provide the ability to edit the maps based on points feature matching by providing a method which further includes displaying, within the user interface, a plurality of suggested commands for altering positioning of the first set of point cloud data in 3D virtual space in order to better match at least the first subset of points with the second subset of points as suggested by paragraph [0099] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 13.
As per claim 14, SCHMITT in view of ZHANG discloses the non-transitory computer-readable medium of claim 13. SCHMITT fails to disclose wherein each inlier feature match comprises a feature correspondence pair having a first point in the query point cloud and a second point in the reference point cloud that are within a predetermined distance threshold of each other.
ZHANG discloses wherein each inlier feature match comprises a feature correspondence pair having a first point in the query point cloud and a second point in the reference point cloud that are within a predetermined distance threshold of each other (the computing system is further adapted to provide the system may identify two or more point clouds that have edges that are misaligned by less than a threshold distance wherein the threshold is adjustable for example to, 0.1, 0.5, 1, etc. in the x axis, y axis, and/or z axis; paragraphs [0056-0058], [0085]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have wherein each inlier feature match comprises a feature correspondence pair having a first point in the query point cloud and a second point in the reference point cloud that are within a predetermined distance threshold of each other of ZHANG reference. The Suggestion/motivation for doing so would have been to provide to the user the ability to perform spatial manipulation is determined based at least in part on a determination that the first set of point cloud data and the second set of point cloud data are misaligned by less than a threshold, wherein the threshold represents at least one of a distance or an angle as suggested by paragraph [00103] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 14.
As per claim 16, SCHMITT discloses the system of claim 15. SCHMITT fails to disclose wherein the operations further comprise: selecting, based on geolocation data obtained from one or more geolocation sensor devices of the vehicle at commencement of an activation sequence of the vehicle, a map tile comprising a predefined geographical area that includes an initial location of the vehicle from a plurality of map tiles in the HD map; and obtaining the reference point cloud from the selected map tile in the HD map.
ZHANG discloses wherein the operations further comprise: selecting, based on geolocation data obtained from one or more geolocation sensor devices of the vehicle at commencement of an activation sequence of the vehicle (the computing system is adapted to provide geographic location data related to sensors resident on the vehicle various radar sensors and allow for real time position /location data relating to the vehicle in relation to the generated map and travel path; paragraphs [0028], [0032], [0082], [0091]; Claim 15), a map tile comprising a predefined geographical area that includes an initial location of the vehicle from a plurality of map tiles in the HD map (the computing system is adapted to provide geographic location data related to map data 154 which allows for generation of a 3D map which depicts and shows various street elements including layout of streets, buildings, road details and information, land marks, intersections, bridges, and various other map points of interest; paragraphs [0028], [0082], [0091]; Claim 15); and obtaining the reference point cloud from the selected map tile in the HD map (the computing device in communication with server 130 can transmit the map data 154 to a vehicle 120 for storage therein in the on vehicle data store 129; paragraphs [0032-0033], [0056-0061]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have the operations further comprise: selecting, based on geolocation data obtained from one or more geolocation sensor devices of the vehicle at commencement of an activation sequence of the vehicle, a map tile comprising a predefined geographical are of ZHANG reference. The Suggestion/motivation for doing so would have been to provide various user interface tools and associated computer functionality that enables integrated visual exploration and editing with respect to both two-dimensional (2D) and three-dimensional (3D) visualizations of captured LiDAR data, pose graphs, and map data in order to build more accurate HD maps according to paragraph [0015] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 16.
As per claim 17, SCHMITT discloses the system of claim 15. SCHMITT fails to disclose wherein the operations further comprise: down sampling voxels in the query point cloud and the reference point cloud; and deriving a surface normal for each of the query point cloud and the reference point cloud.
ZHANG discloses wherein the operations further comprise: down sampling voxels in the query point cloud and the reference point cloud (the computing system provides a user interface via which the user may down scale/ zoom in a 2D map projection of a 3D point cloud rendering if the zoom scale meets a predefined threshold; paragraphs [0072], [0082-0084]; figures 4 and 8); and deriving a surface normal for each of the query point cloud and the reference point cloud (data processing system 123 provides processed data 162 to the vehicle control system 126 to respond to point-to-point activity in the surroundings of the vehicle 120, processed data 162 is comparisons between the raw sensor data 161 representing an operational environment of the vehicle 120, which is continuously monitored via sensor array 121-and the map data stored in the data store 129, further the data processing system 123 is programmed with machine learning or other artificial intelligence capabilities to enable the vehicle 120 to identify and respond to conditions, events, and/or potential hazards on a surface such as a road while driving in traffic; paragraphs [0052]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have down sampling voxels in the query point cloud and the reference point cloud of ZHANG reference. The Suggestion/motivation for doing so would have been to provide on board localization of the vehicle in the environment allowing vehicle to become aware of an instant location and orientation of the vehicle in comparison to the stored map data in order to maneuver the vehicle on surface streets through traffic and assist a driver in maneuvering the vehicle on surface streets through traffic and identify and respond to potential hazards or local conditions, such as weather or traffic conditions as suggested at paragraph [0052] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 17.
As per claim 19, SCHMITT discloses the system of claim 15. SCHMITT fails to disclose wherein the operations further comprise: generating the plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud by pairing each point in the query point cloud with a closest neighboring point in the reference point cloud.
ZHANG discloses wherein the operations further comprise: generating the plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud by pairing each point in the query point cloud with a closest neighboring point in the reference point cloud (the computing system is adapted to provide over said user interfaces for viewing HD maps at different levels, exploring 3D point clouds of a certain part of an HD map, measuring the distance between two points from maps or point clouds from related positions, and tuning parts of a map to better align or match (pair) two or more point clouds; paragraphs [0056-0058]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have generating the plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud by pairing each point in the query point cloud with a closest neighboring point in the reference point cloud of ZHANG reference. The Suggestion/motivation for doing so would have been to provide positioning algorithms such as an iterative closest point ICP algorithm to perform the dimensional analysis steps in order to allow for higher accuracy in the map models which are developed and will allow the user to in the user interface 300 enable scrolling, panning, rotating, selecting, and zooming in either view provided as suggested by paragraphs [0069-0071 of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 19.
As per claim 20, SCHMITT discloses the system of claim 15. SCHMITT fails to disclose wherein the determining the coarse alignment further comprises: determining a number of inlier feature matches for each solution in the plurality of solutions, wherein each inlier feature match comprises a feature correspondence pair having a first point in the query point cloud and a second point in the reference point cloud that are within a predetermined distance threshold of each other; and identifying the solution with the highest number of inlier feature matches as the coarse alignment.
ZHANG discloses wherein the determining the coarse alignment further comprises: determining a number of inlier feature matches for each solution in the plurality of solutions, wherein each inlier feature match comprises a feature correspondence pair having a first point in the query point cloud and a second point in the reference point cloud that are within a predetermined distance threshold of each other (the computing devices are adapted to further provide options, via the user interface, to select a command and an associated scale for the command, wherein the scale represents a numeric amount of at least one of: movement, yaw, pitch or roll and further the suggested commands can include movement along each of an x axis, y axis and z axis; paragraphs [0102-0105]); and identifying the solution with the highest number of inlier feature matches as the coarse alignment (the user interface operations comprise automatically determining a suggested spatial manipulation of the first set of point cloud data to better match at least the first subset of points with the second subset of points by automatically applying the suggested spatial manipulation within the 3D rendering displayed in the user interface, pending user approval of the suggested spatial manipulation the manipulation is determined based at least in part on a determination that the first set of point cloud data and the second set of point cloud data are misaligned by less than a threshold, wherein the threshold represents at least one of a distance or an angle feature; paragraphs [0102-0105]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have determining a number of inlier feature matches for each solution in the plurality of solutions of ZHANG reference. The Suggestion/motivation for doing so would have been to provide the ability to edit the maps based on points feature matching by providing a method which further includes displaying, within the user interface, a plurality of suggested commands for altering positioning of the first set of point cloud data in 3D virtual space in order to better match at least the first subset of points with the second subset of points as suggested by paragraph [0099] of ZHANG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHANG with SCHMITT to obtain the invention as specified in claim 20.
Claims 4, 11, and 18 are rejected under 35 § U.S.C. 103 as being obvious over US 2018/0341021 A1 to SCHMITT et al. (hereinafter “SCHMITT”) in view of US 2023/0204363 A1 to TIIRA (hereinafter “TIIRA”).
As per claim 4, SCHMITT discloses the method of claim 1. SCHMITT fails to disclose wherein the extracting the first set of features from the query point cloud and the second set of features from the reference point cloud further comprises: deriving, by the one or more computing devices, at least one fast point feature histogram “FPFH” descriptor for every point in the query point cloud and the reference point cloud.
TIIRA discloses wherein the extracting the first set of features from the query point cloud and the second set of features from the reference point cloud further comprises: deriving, by the one or more computing devices, at least one fast point feature histogram “FPFH” descriptor for every point in the query point cloud and the reference point cloud (the features may be extracted from the point clouds of interest by generating histograms related to the obtained lidar data, wherein the histogram provides a fast and accurate scan registration through minimization of the distance between compact 3D NDT representations, of points in the point clouds; abstract; fig 2; paragraphs [0046-0048], [0062]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have deriving at least one fast point feature histogram (FPFH) descriptor for every point in the query point cloud and the reference point cloud of TIIRA reference. The Suggestion/motivation for doing so would have been to provide the ability to identify common upward pointing linear shaped features such trees and poles are clustered in a single histogram bin relating to point clouds obtained via LIDAR as suggested by TIIRA at paragraph [0048]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine TIIRA with SCHMITT to obtain the invention as specified in claim 4.
As per claim 11, SCHMITT discloses the non-transitory computer-readable medium of claim 8. SCHMITT fails to disclose wherein the extracting the first set of features from the query point cloud and the second set of features from the reference point cloud further comprises: deriving at least one fast point feature histogram (FPFH) descriptor for every point in the query point cloud and the reference point cloud.
TIIRA discloses wherein the extracting the first set of features from the query point cloud and the second set of features from the reference point cloud further comprises: deriving at least one fast point feature histogram (FPFH) descriptor for every point in the query point cloud and the reference point cloud (the features may be extracted from the point clouds of interest by generating histograms related to the obtained lidar data, wherein the histogram provides a fast and accurate scan registration through minimization of the distance between compact 3D NDT representations, of points in the point clouds; abstract; fig 2; paragraphs [0046-0048], [0062]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have deriving at least one fast point feature histogram (FPFH) descriptor for every point in the query point cloud and the reference point cloud of TIIRA reference. The Suggestion/motivation for doing so would have been to provide the ability to identify common upward pointing linear shaped features such trees and poles are clustered in a single histogram bin relating to point clouds obtained via LIDAR as suggested by TIIRA at paragraph [0048]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine TIIRA with SCHMITT to obtain the invention as specified in claim 11.
As per claim 18, SCHMITT discloses the system of claim 15. SCHMITT fails to disclose wherein the extracting the first set of features from the query point cloud and the second set of features from the reference point cloud further comprises: deriving at least one fast point feature histogram (FPFH) descriptor for every point in the query point cloud and the reference point cloud.
TIIRA discloses wherein the extracting the first set of features from the query point cloud and the second set of features from the reference point cloud further comprises: deriving at least one fast point feature histogram (FPFH) descriptor for every point in the query point cloud and the reference point cloud (the features may be extracted from the point clouds of interest by generating histograms related to the obtained lidar data, wherein the histogram provides a fast and accurate scan registration through minimization of the distance between compact 3D NDT representations, of points in the point clouds; abstract; fig 2; paragraphs [0046-0048], [0062]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify SCHMITT to have deriving at least one fast point feature histogram (FPFH) descriptor for every point in the query point cloud and the reference point cloud of TIIRA reference. The Suggestion/motivation for doing so would have been to provide the ability to identify common upward pointing linear shaped features such trees and poles are clustered in a single histogram bin relating to point clouds obtained via LIDAR as suggested by TIIRA at paragraph [0048]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine TIIRA with SCHMITT to obtain the invention as specified in claim 18.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. These prior arts include the following:
US 8,736,818 B2
US 8,306,273 B1
US 2024/0027622 A1
US 2018/0074203 A1
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DEVIN JACOB DHOOGE whose telephone number is (571) 270-0999. The examiner can normally be reached 7:30-5:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Bee can be reached on (571) 270-5183. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800- 786-9199 (IN USA OR CANADA) or 571-272-1000.
/Devin Dhooge/
USPTO Patent Examiner
Art Unit 2677
/ANDREW W BEE/Supervisory Patent Examiner, Art Unit 2677