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
1. Applicant’s response received has been fully considered and entered.
Response to Arguments
2. Applicant’s amendment and the related arguments with respect to claim 1 have been considered. The instant application is rejected on new grounds of rejection while considering the newly
amended limitations.
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) 1-3, 7-12, 16-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. US20210333406A1, “Lee”, in view of Peake et al., US20200074266A1 “Peake”, further in view of Zhang “Autonomous Valet Parking (AVP) Project with F1/10 Cars”, medium, https://medium.com/@zzang/autonomous-valet-parking-avp-project-with-f1-10-cars-f7046a1e0997 Apr. 2020, “Zhang”.
Regarding claim 1, LEE discloses an apparatus (LEE, abstract) comprising: a light detection (LEE claim 1) and ranging (LiDAR) data collector (LEE¶ 46)
It is noted that LEE is silent about Lidar and Data collectors installed on a vehicle configured to be driven in a real environment to collect LiDAR data; a database configured to store the collected LiDAR data; a virtual environment generation engine configured to generate a virtual environment; and a LiDAR data generator configured to generate virtual LiDAR data corresponding to a movement of a virtual vehicle in the generated virtual environment as claimed.
However, PEAKE discloses Lidar and Data collectors (PEAKE, ¶ 39) installed on a vehicle configured to be driven in a real environment to collect LiDAR data (PEAKE, ¶ [0040], In still further implementations, the virtual environment may be at least partially generated based on geo-spatial data. Such geo-spatial data may be sourced from predefined or existing images or other geo-spatial data (e.g., height maps or geo-spatial semantic data such as road versus terrain versus building data) as retrieved from remote sources (e.g., Mapbox images, Google Maps images, etc.). For example, the geo-spatial data may be used as a starting point to construct detailed representations of roads, lanes for the roads, and/or other objects or surfaces within the virtual environment. If previously collected image or depth data is available for a particular region of the virtual environment, then the system also can use real-world lidar data, and/or use techniques such as SLAM or photogrammetry to construct the virtual environment to provide additional real-world detail not specified by the m); a database configured to store the collected LiDAR data (PEAKE, ¶ 49, i.e., … In some embodiments, the memory(s) may store information or other data as described herein in a database (e.g., a relational database, such as Orcale, DB2, MySQL, or a NoSQL based database, such as MongoDB). The data stored in memory 152 may include all or part of any of the data or information described herein, including, for example, the photo-realistic scenes, the depth-map-realistic scenes, the environment-object data, feature training dataset(s), or other information or scenes as described herein.); a virtual environment generation engine configured to generate a virtual environment (PEAKE, ¶ 7); and a LiDAR data generator configured to generate virtual LiDAR data corresponding to a movement of a virtual vehicle in the generated virtual environment (PEAKE, ¶ 11);
a point cloud map generator configured to generate a point cloud map based on the collected LiDAR data (PEAKE, ¶ 50);
wherein the point cloud map comprises the collected LiDAR data that is stored in association with corresponding coordinates on the virtual environment (PEAKE, ¶ 104).
Both LEE and PEAKE teach systems with Lidar, and those systems are comparable to that of the instant application. Because the two cited references are analogous to the instant application, it 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, to include in the LEE disclosure, database associating with a virtual reality map, as taught by PEAKE. Such inclusion would have increased the usefulness of the system by generating feature training datasets for use in real-world autonomous driving applications, and would have been consistent with the rationale of combining prior art elements according to known methods to yield predictable results to show a prima facie case of obviousness (MPEP 2143(I)(A)) under KSR International Co. v. Teleflex Inc., 127 S. Ct. 1727, 82 USPQ2d 1385, 1395-97 (2007);
It is noted that LEE/PEAKE is silent about a point cloud map generator configured to: generate a plurality of four-dimensional points by adding, based on the collected LiDAR data, intensity value information at corresponding coordinates to three-dimensional (3D) coordinate information in the virtual environment; and create, using the plurality of four-dimensional points, a point cloud map;a mesh converter configured to convert the point cloud map into a 3D mesh map by connecting one or more points of the point cloud map as claimed.
However ZHANG discloses a point cloud map generator (ZHANG, pg. 6, i.e. x, y, z and I -reflectance, pillar feature ) configured to: generate a plurality of four-dimensional points by adding, based on the collected LiDAR data, intensity value information (i.e. reflectance is the intensity information, as it is proportional to the light reflected in the situation) at corresponding coordinates to three-dimensional (3D) coordinate information in the virtual environment; and create, using the plurality of four-dimensional points, a point cloud map (i.e. as cited above, pillar feature); a mesh converter configured to convert the point cloud map into a 3D mesh map by connecting one or more points of the point cloud map (as cited above, and pg. 7, fig. 4); a movement of a virtual vehicle in a portion of the generated virtual environment corresponding to the 3D mesh map (ZHANG, pg. 8, and ZHANG, pg. 8, Fig. 5).
Both LEE/PEAKE and ZHANG teach systems with Lidar, and those systems are comparable to that of the instant application. Because the two cited references are analogous to the instant application, it 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, to include in the LEE/PEAKE disclosure, a 4d meshed map by addition of intensity of the light reflected from the object, as taught by ZHANG. Such inclusion would have increased the usefulness of the system by making valet parking service more efficient and affordable, and would have been consistent with the rationale of combining prior art elements according to known methods to yield predictable results to show a prima facie case of obviousness (MPEP 2143(I)(A)) under KSR International Co. v. Teleflex Inc., 127 S. Ct. 1727, 82 USPQ2d 1385, 1395-97 (2007).
Regarding claim 2, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the apparatus according to claim 1, wherein the LiDAR data collector comprises a laser light emitter and a laser light receiver (PEAKE, ¶ 39), and the collected LiDAR data comprises intensity information of laser light that is emitted from the laser light emitter and reflected off from an object (LEE¶ 51).
Regarding claim 3, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the apparatus according to claim 2, wherein the intensity information is stored in association with corresponding coordinate information of a point where the laser light is reflected (PEAKE, ¶ 72, i.e…. An intensity value may correspond to the intensity of scattered light received at the lidar sensor, and a reflectivity value may correspond to the reflectivity of an object or surface in the virtual environment. In such embodiments, the intensity or reflectivity values may represent one or more virtual lidar sensors, e.g., of a virtual autonomous vehicle such as vehicle 700 or 760, which may simulate one or more real-world lidar sensors as described herein.)
Regarding claim 7, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the apparatus according to claim 6, wherein the LiDAR data generator is configured to: generate virtual laser light emitted to a predetermined mesh of the 3D mesh map (as cited below, i.e. PEAKE, ¶ 83 …Together, geo-spatial data and its related metadata may be used by the automated training dataset generator 100 and/or geo-spatial component to render such data within a virtual environment into a detailed roadway that has realistic lanes and shoulders, etc. For example, in such embodiments, geo-spatial metadata may define a four-lane, two-way highway with a particular width and particular waypoints which may be rendered by the automated training dataset generator 100 and/or geo-spatial component into virtual four lane highway mesh suitable for simulation with a virtual environment (e.g., the virtual environment of scene 400); calculate virtual intensity of laser light associated with reflection of the virtual laser light (PEAKE, ¶ 83).
Regarding claim 8, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the apparatus according to claim 7, wherein the virtual intensity is calculated based on intensity information associated with the predetermined mesh (PEAKE, see the mesh citation above).
Regarding claim 9, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the apparatus according to claim 8, wherein the virtual intensity is calculated as an average of the intensity information associated with the predetermined (ZHANG, i.e. point cloud with the intensity) mesh (PEAKE, see intensity citation above).
Regarding claim 10, LEE/PEAKE/ZHANG, for the same motivation of combination, discloses a method performed by an apparatus, the method comprising: receiving, from a light detection and ranging (LiDAR) data collector installed on a vehicle configured to be driven in a real environment, collected LiDAR data; storing the collected LiDAR data in a database; generating, by using a virtual environment generation engine, a virtual environment; and generating virtual LiDAR data corresponding to a movement of a virtual vehicle on the generated virtual environment (see rejection of claim 1). The other amended features have similar limitations as the amendments to the claim 1, thus see rejection of claim 1.
Regarding claim 11, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the method according to claim 10, wherein the collected LiDAR data comprises intensity information of laser light that is emitted from a laser light emitter and reflected off from an object (see Lidar citation above)
Regarding claim 12, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the method according to claim 11, wherein the intensity information is stored in association with corresponding coordinate information of a point where the laser light is reflected (see the point citation above)
Regarding claim 16, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the method according to claim 15, wherein the generating the virtual LiDAR data comprises: generating virtual laser light emitted to a predetermined mesh of the converted 3D mesh map; calculating virtual intensity of laser light associated with reflection of the emitted virtual laser light (see virtual lidar citation above)
Regarding claim 17, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the method according to claim 16, wherein the virtual intensity is calculated based on intensity information associated with the predetermined mesh (see mesh citation above).
Regarding claim 18, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the method according to claim 17, wherein the virtual intensity is calculated as an average of the intensity information associated with the predetermined mesh (see virtual citation above)
Regarding claim 19, LEE/PEAKE/ZHANG, for the same motivation of combination, discloses an apparatus comprising: a receiver configured to receive light detection and ranging (LiDAR) data from a vehicle configured to be driven in a real environment to collect the LiDAR data; a database configured to store the LiDAR data; a virtual environment generation engine configured to generate a virtual environment; and a LiDAR data generator configured to generate virtual LiDAR data corresponding to a movement of a virtual vehicle in the generated virtual environment (see rejection of claim 1); The other amended features have similar limitations as the amendments to the claim 1, thus see rejection of claim 1.
Regarding claim 20, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the apparatus according to claim 19, wherein the collected LiDAR data comprises intensity information of laser light that is emitted from a laser light emitter and reflected off from an object (PEAKE, ¶ 72).
Regarding claim 21, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the apparatus according to claim 20, wherein the intensity information is stored in association with corresponding coordinate information of a point where the laser light is reflected (PEAKE, ¶ 72, i.e…. An intensity value may correspond to the intensity of scattered light received at the lidar sensor, and a reflectivity value may correspond to the reflectivity of an object or surface in the virtual environment. In such embodiments, the intensity or reflectivity values may represent one or more virtual lidar sensors, e.g., of a virtual autonomous vehicle such as vehicle 700 or 760, which may simulate one or more real-world lidar sensors as described herein.)
Regarding claim 22, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the apparatus according to claim 19, wherein the instructions, when executed by the one or more processors, cause the apparatus to generate the virtual LiDAR data by causing the apparatus to:
generate virtual laser light emitted to a predetermined mesh of the 3D mesh map (as cited below, i.e. PEAKE, ¶ 83 …Together, geo-spatial data and its related metadata may be used by the automated training dataset generator 100 and/or geo-spatial component to render such data within a virtual environment into a detailed roadway that has realistic lanes and shoulders, etc. For example, in such embodiments, geo-spatial metadata may define a four-lane, two-way highway with a particular width and particular waypoints which may be rendered by the automated training dataset generator 100 and/or geo-spatial component into virtual four lane highway mesh suitable for simulation with a virtual environment (e.g., the virtual environment of scene 400); calculate virtual intensity of laser light associated with reflection of the virtual laser light (PEAKE, ¶ 83)
Regarding claim 23, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the apparatus according to claim 22, wherein the virtual intensity is calculated based on intensity information associated with the predetermined mesh (PEAKE, see the mesh citation above).
Regarding claim 24, LEE/PEAKE/ZHANG, for the same motivation of combination, further discloses the apparatus according to claim 23, wherein the virtual intensity is calculated as an average (ZHANG, pg. 6, i.e. reflectance is average of the intensity) of the intensity information associated with the predetermined mesh (PEAKE, ¶ 83).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
wherein a mesh converter configured to convert the point cloud map into a three-dimensional (3D) mesh map (see point cloud citation above).
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Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANK F HUANG whose telephone number is (571)272-0701. The examiner can normally be reached Monday-Friday, 8:30 am - 6:00 pm (Eastern Time), Federal Alternative First Friday Off.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jay Patel can be reached at (571)272-2988.. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/FRANK F HUANG/Primary Examiner, Art Unit 2485
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