DETAILED ACTION
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 .
Continued Examination
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's Amendment with a Request for Continued Examination filed on June 17, 2026 has been entered.
Response to Arguments
Applicant's arguments and amendments in the Amendment, with respect to the rejection(s) of claim(s) 2, 9 and 16 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Fu et al., "Commodity 3D display based on point cloud reconstruction," 2018 Chinese Control And Decision Conference (CCDC), Shenyang, China, 2018, pp. 5617-5622, doi: 10.1109/CCDC.2018.8408111.
Applicant's arguments and amendments filed in the Amendment regarding the rejection of claims 2-21 under obviousness-type double patenting have been fully considered but they are not persuasive. The claims amendments adding additional subject matter are also recited in the US Patent No. 11,460,580 of the parent application to the present application, and therefore, the ODP rejection is maintained with updates to the rejection rationale provided herein to reflect the new claim amendments.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 2–21 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1–3, and 17–18 of U.S. Patent No. 11,460,580 B2 (herein ‘580) in view of Egger et al., "PoseMap: Lifelong, Multi-Environment 3D LiDAR Localization," 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018, pp. 3430-3437, doi: 10.1109/IROS.2018.8593854 (herein “Egger”).
Regarding claims 2–6 of the present application, these claims correspond to claim 1 of ‘580 as follows:
Claim 2 limitations from the present application, deficiencies of ‘580 noted in square brackets
Claim 1 limitation from ‘580
A method comprising: determining a nearest neighbor correspondence between one or more individual first points of a first point cloud corresponding to [at least one first sensor scan] of a region and one or more individual second points of a second point cloud corresponding to [at least one second sensor scan] of the region
A computer-implemented method, comprising: receiving a search query, the search query specifying a search space comprising a query-point and a search range, the query-point being included in a first point cloud comprising a first set of three-dimensional (3D) points that correspond to at least a portion of a region; accessing a compressed octree representation of a second point cloud comprising a second set of 3D points that correspond to the region, the compressed octree representation comprising nodes, at least some of the nodes storing a sibling link to a sibling node having the same parent node; … identifying at least one nearest neighbor node in a set of leaf nodes identified, by the traversing operations, as corresponding to the search space
the determining of the nearest neighbor correspondence including using the one or more individual first points as corresponding one or more query points for traversing a compressed octree representation of the second point cloud to identify one or more nodes of the compressed octree representation that correspond to points of the second point cloud that are nearest neighbor points of the one or more individual first points;
a query-point and a search range, the query-point being included in a first point cloud comprising a first set of three-dimensional (3D) points that correspond to at least a portion of a region; accessing a compressed octree representation of a second point cloud comprising a second set of 3D points that correspond to the region, the compressed octree representation comprising nodes, at least some of the nodes storing a sibling link to a sibling node having the same parent node; traversing the compressed octree representation to identify one or more nodes that correspond to the search space, the traversing comprising selecting a current node of the compressed octree representation and performing traversing operations, the traversing operations including: responsive to determining that the current node is a leaf node and that one or more coordinates associated with the current node are included in the search space, marking the current node as corresponding to the search space, responsive to determining that the current node is not a leaf node and determining that one or more coordinates associated with the current node are included in the search space, identifying a child node of the current node and performing the traversing operations with respect to the identified child node in which the identified child node is selected as the next current node used in the traversing operations, … identifying at least one nearest neighbor node in a set of leaf nodes identified, by the traversing operations, as corresponding to the search space
determining [a location of a machine] within the region based at least on the correspondence;
identifying at least one nearest neighbor node in a set of leaf nodes identified, by the traversing operations, as corresponding to the search space
performing one or more [control] operations [with respect to the machine based at least on the location].
using the query point and a particular second point of the second point cloud that corresponds to the at least one nearest neighbor node for performing an operation.
Claim 1 from ‘580 does not recite that the performing an operation is a “control” operation, or that the identified node corresponding to the search space is “a location of a machine” that the operation is performed “with respect to the machine based at least on the location,” or that the point clouds are from sensor scans. However, Egger teaches determining a location of a machine (Egger page 3430, and Abstract, localizing (determining a location) for a vehicle (machine) within a map (the region) by obtaining the closest map nodes to map features determined by LIDAR sensing (the correspondence)), control operations with respect to the machine based at least on the location (Egger page 3430, and Abstract, waypoint navigation in response to localization determination, the waypoint navigation involving moving a vehicle (performing one or more control operations) along predefined routes within a certain area), and point clouds from sensor scans (Egger page 3430, a number of sensors providing vehicle position in a map using SLAM (point cloud)).
Therefore, taking the recitations of Claim 1 from ‘580 and the teachings of Egger together as a whole, it would have been obvious to a person having ordinary skill in the art (herein “PHOSITA”) before the effective filing date of the claimed invention to have modified claim 1 of ‘580 to include the localization and thereafter waypoint navigation as disclosed in Egger at least because doing so would provide autonomous driving capabilities with high accuracy in navigation. See Egger Abstract.
Claim 3 limitations from the present application
Claim 1 limitation from ‘580
wherein the traversing of the compressed octree representation is based at least on a search space that is defined based at least on the one or more query points
the search query specifying a search space comprising a query-point and a search range, the query-point being included in a first point cloud comprising a first set of three-dimensional (3D) points that correspond to at least a portion of a region; accessing a compressed octree representation of a second point cloud comprising a second set of 3D points that correspond to the region … traversing the compressed octree representation to identify one or more nodes that correspond to the search space, the traversing comprising selecting a current node of the compressed octree representation and performing traversing operations, the traversing operations including: responsive to determining that the current node is a leaf node and that one or more coordinates associated with the current node are included in the search space, marking the current node as corresponding to the search space
and a search range around one or more point locations in the region that correspond to the one or more query points.
the search query specifying a search space comprising a query-point and a search range, the query-point being included in a first point cloud comprising a first set of three-dimensional (3D) points that correspond to at least a portion of a region;
Claim 4 limitations from the present application
Claim 1 limitation from ‘580
wherein the traversing of the compressed octree representation includes selecting a particular node of the compressed octree representation
the traversing comprising selecting a current node of the compressed octree representation and performing traversing operations
and performing one or more traversing operations with respect to the particular node based at least on the search space.
the traversing operations including: responsive to determining that the current node is a leaf node and that one or more coordinates associated with the current node are included in the search space, marking the current node as corresponding to the search space
Claim 5 limitations from the present application
Claim 1 limitation from ‘580
wherein the one or more traversing operations include one or more of: marking the particular node as corresponding to an area within the region that corresponds to the one or more query points responsive to the particular node being determined to be a leaf node and responsive to a determination that one or more coordinates associated with a current node correspond to the search space; responsive to a determination that the particular node is not a leaf node and responsive to the determination that one or more coordinates associated with the particular node correspond to the search space, identifying a child node of the particular node and performing the one or more traversing operations with respect to the identified child node in which the identified child node is selected as the next particular node used in the one or more traversing operations; or responsive to determining that no coordinates associated with the particular node correspond to the search space, identifying a sibling node of the particular node and performing the one or more traversing operations with respect to the identified sibling node in which the identified sibling node is selected as the next particular node used in the one or more traversing operations.
the search query specifying a search space comprising a query-point and a search range, the query-point being included in a first point cloud comprising a first set of three-dimensional (3D) points that correspond to at least a portion of a region; accessing a compressed octree representation of a second point cloud comprising a second set of 3D points that correspond to the region … responsive to determining that the current node is a leaf node and that one or more coordinates associated with the current node are included in the search space, marking the current node as corresponding to the search space, responsive to determining that the current node is not a leaf node and determining that one or more coordinates associated with the current node are included in the search space, identifying a child node of the current node and performing the traversing operations with respect to the identified child node in which the identified child node is selected as the next current node used in the traversing operations and responsive to determining that no coordinates associated with the current node are included in the search space, identifying a sibling node of the current node using a corresponding sibling link of the current node and performing the traversing operations with respect to the identified sibling node in which the identified sibling node is selected as the next current node used in the traversing operations
Claim 6 limitations from the present application
Claim 1 limitation from ‘580
wherein no traversing operations are performed for any child node of the particular node responsive to determining that no coordinates associated with the particular node correspond to the search space.
and in which no traversing operations are performed for any child node of the current node responsive to determining that no coordinates associated with the current node are included in the search space
Regarding claims 7–8 of the present application, these claims correspond to claims 1 and/or claims 2–3 of ‘580 as follows:
Claim 7 limitations from the present application
Claims 1 and 3 limitations from ‘580
wherein the identifying of the sibling node of the particular node is based at least on a sibling link corresponding to the particular node, the sibling link storing an index of the sibling node, the index identifying the sibling node in a linear array.
Claim 1: identifying a sibling node of the current node using a corresponding sibling link of the current node
Claim 3 (depends from claim 1): wherein the sibling link stores an index of the sibling node, the index identifying the sibling node in a linear array.
Claim 8 limitations from the present application
Claim 2 limitations from ‘580
wherein the traversing of the compressed octree representation is performed without decompressing the compressed octree representation.
wherein the traversing operations are performed directly on the compressed octree representation without having to decompress the compressed octree representation.
Regarding claims 9–14, and 16-20 of the present application, these claims correspond to claim 17 of ‘580 as follows:
Claim 9 and 16 limitations from the present application, deficiencies of ‘580 noted in square brackets
Claim 17 limitation from ‘580
A system comprising: one or more processing units to cause performance of operations, the operations comprising: (claim 9)
A processor comprising processing circuitry to cause performance of operations, the operations comprising: (claim 16)
determining a correspondence with respect to a first point cloud obtained from [at least one first sensor scan] and a compressed octree representation of a second point cloud obtained from [at least one second sensor scan], the determining of the correspondence being based at least on using one or more individual first points of the first point cloud as corresponding one or more query points for traversing the compressed octree representation
A computer system comprising: one or more processors; and one or more non-transitory computer readable media storing instructions that in response to being executed by the one or more processors, cause the computer system to perform operations, the operations comprising: receiving a search query, the search query specifying a search space comprising a query-point and a search range; (Examiner Note: the query point and search range defining a first point cloud) accessing a compressed octree representation of a point cloud comprising three-dimensional (3D) points of a region (Examiner note this maps to the second point cloud), the compressed octree representation comprising nodes, at least some of the nodes storing a sibling link to a sibling node having the same parent node; traversing the compressed octree representation to identify one or more nodes that correspond to the search space
to identify one or more nodes of the compressed octree representation that correspond to a same area as one or more points included in the first point cloud;
traversing the compressed octree representation to identify one or more nodes that correspond to the search space … determining that one or more coordinates associated with the current node are included in the search space
performing one or more [control] operations [with respect to a machine based at least on the correspondence].
using the at least one nearest neighbor node for performing an operation on the point cloud
Claim 17 from ‘580 does not recite that the performing an operation is a “control” operation, that the operation is performed “with respect to the machine based at least on the location,” or that the point clouds are from sensor scans. However, Egger teaches control operations with respect to the machine based at least on the location (Egger page 3430, and Abstract, waypoint navigation in response to localization determination, the waypoint navigation involving moving a vehicle (performing one or more control operations) along predefined routes within a certain area), and point clouds from sensor scans (Egger page 3430, a number of sensors providing vehicle position in a map using SLAM (point cloud)).
Therefore, taking the recitations of Claim 17 from ‘580 and the teachings of Egger together as a whole, it would have been obvious to a person having ordinary skill in the art (herein “PHOSITA”) before the effective filing date of the claimed invention to have modified claim 17 of ‘580 to include the localization and thereafter waypoint navigation as disclosed in Egger at least because doing so would provide autonomous driving capabilities with high accuracy in navigation. See Egger Abstract.
Claim 10 limitations from the present application, deficiencies of ‘580 noted in square brackets
Claim 17 limitation from ‘580
wherein the performing of the one or more [control operations with respect to the machine] based at least on the correspondence is [based at least on a location of the machine] that is determined based at least on the correspondence.
using the at least one nearest neighbor node for performing an operation on the point cloud
Claim 17 from ‘580 does not recite that the performing an operation is a “control” operation, or that the identified node corresponding to the search space is “a location of a machine.” However, Egger teaches determining a location of a machine (Egger page 3430, and Abstract, localizing (determining a location) for a vehicle (machine) within a map (the region) by obtaining the closest map nodes to map features determined by LIDAR sensing (the correspondence)), control operations with respect to the machine based at least on the location (Egger page 3430, and Abstract, waypoint navigation in response to localization determination, the waypoint navigation involving moving a vehicle (performing one or more control operations) along predefined routes within a certain area).
Therefore, taking the recitations of Claim 1 from ‘580 and the teachings of Egger together as a whole, it would have been obvious to a person having ordinary skill in the art (herein “PHOSITA”) before the effective filing date of the claimed invention to have modified claim 1 of ‘580 to include the localization and thereafter waypoint navigation as disclosed in Egger at least because doing so would provide autonomous driving capabilities with high accuracy in navigation. See Egger Abstract.
Claims 11 and 17 limitations from the present application
Claim 17 limitation from ‘580
wherein the traversing of the compressed octree representation is based at least on a search space that corresponds to the area
a search space comprising a query-point and a search range …
traversing the compressed octree representation to identify one or more nodes that correspond to the search space
and that is defined based at least on {the one or more query points – claim 11 / an individual first point included in the first point cloud – claim 17} and a search range around one or more point locations that correspond to the {one or more query points – claim 11 / first point – claim 17}.
the search query specifying a search space comprising a query-point and a search range; accessing a compressed octree representation of a point cloud comprising three-dimensional (3D) points of a region, the compressed octree representation comprising nodes, at least some of the nodes storing a sibling link to a sibling node having the same parent node; traversing the compressed octree representation to identify one or more nodes that correspond to the search space
Claims 12 and 18 limitations from the present application
Claim 17 limitation from ‘580
wherein the traversing of the compressed octree representation includes selecting a particular node of the compressed octree representation
the traversing comprising selecting a current node of the compressed octree representation and performing traversing operations
and performing one or more traversing operations with respect to the particular node based at least on the search space.
the traversing operations including: responsive to determining that the current node is a leaf node and that one or more coordinates associated with the current node are included in the search space, marking the current node as corresponding to the search space
Claims 13 and 19 limitations from the present application
Claim 17 limitation from ‘580
wherein the one or more traversing operations include one or more of: marking the particular node as corresponding to the area responsive to the particular node being determined to be a leaf node and responsive to a determination that one or more coordinates associated with a current node correspond to the search space; responsive to a determination that the particular node is not a leaf node and responsive to the determination that one or more coordinates associated with the particular node correspond to the search space, identifying a child node of the particular node and performing the one or more traversing operations with respect to the identified child node in which the identified child node is selected as the next particular node used in the one or more traversing operations; or responsive to determining that no coordinates associated with the particular node correspond to the search space, identifying a sibling node of the particular node and performing the one or more traversing operations with respect to the identified sibling node in which the identified sibling node is selected as the next particular node used in the one or more traversing operations.
responsive to determining that the current node is a leaf node and that one or more coordinates associated with the current node are included in the search space, marking the current node as corresponding to the search space, responsive to determining that the current node is not a leaf node and determining that one or more coordinates associated with the current node are included in the search space, identifying a child node of the current node and performing the traversing operations with respect to the identified child node in which the identified child node is selected as the next current node used in the traversing operations and responsive to determining that no coordinates associated with the current node are included in the search space, identifying a sibling node of the current node using a corresponding sibling link of the current node and performing the traversing operations with respect to the identified sibling node in which the identified sibling node is selected as the next current node used in the traversing operations
Claims 14 and 20 limitations from the present application
Claim 17 limitation from ‘580
wherein no traversing operations are performed for any child node of the particular node responsive to determining that no coordinates associated with the particular node correspond to the search space.
and in which no traversing operations are performed for any child node of the current node responsive to determining that no coordinates associated with the current node are included in the search space
Regarding claims 15 and 21 of the present application, these claims correspond to claim 18 of ‘580 as follows:
Claims 15 and 21 limitations from the present application
Claim 18 limitations from ‘580
wherein the traversing of the compressed octree representation is performed without decompressing the compressed octree representation.
wherein the traversing operations are performed directly on the compressed octree representation without having to decompress the compressed octree representation.
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 nonobviousness.
Claims 2–6, and 8–21 are rejected under 35 U.S.C. 103 as being unpatentable over Behley et al., “Efficient Radius Neighbor Search in Three-dimensional Point Clouds,” 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015, pp. 3625-3630, doi: 10.1109/ICRA.2015.7139702 (herein “Behley”) in view of Fu et al., "Commodity 3D display based on point cloud reconstruction," 2018 Chinese Control And Decision Conference (CCDC), Shenyang, China, 2018, pp. 5617-5622, doi: 10.1109/CCDC.2018.8408111, further in view of Egger et al., "PoseMap: Lifelong, Multi-Environment 3D LiDAR Localization," 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018, pp. 3430-3437, doi: 10.1109/IROS.2018.8593854 (herein “Egger”).
Regarding claims 2, 9 and 16 with claim 2 as exemplary, deficiencies of Behley noted in square brackets, and substantive differences between the claims noted in curly brackets {}, { Behley teaches a method comprising – Claim 1 (Behley Abstract, radius neighbor search) / a system comprising: one or more processing units to cause performance of operations, the operations comprising – claim 9 / a processor comprising processing circuitry to cause performance of operations, the operations comprising – claim 16 (Behley Abstract, radius neighbor search, where page 3630 section V discloses GPU (graphics processing unit) based implementations)}
determining a {nearest neighbor – claim 2 only} correspondence {between one or more individual first points of – claim 2 / with respect to - claims 9 and 16} a first point cloud {corresponding to – claims 2 and 16 / obtained from – claim 9} at least one first sensor scan {of a region – claims 2 and 16 only} (Behley page 3625–3626, Algorithm 1, section III, radius neighbors search performed using a query point q that is of a point cloud P (first point cloud), where page 3628 section A - Datasets, teaches the point cloud data being real-world data from laser rangefinder sensor)[{and one or more individual second points – claim 2 / and a [compressed] octree representation – claims 9 and 16} of a second point cloud {corresponding to – claims 2 and 16 / obtained from – claim 9} at least one second sensor scan {of the region – claims 2 and 16 only}],
the determining of the {nearest neighbor – claim 2 only} correspondence {including using the – claim 2 / being based at least on using – claim 9 / including traversing, based at least on – claim 16} one more {individual – claims 2 and 9 only} first points {of the first point cloud – claim 9 only / included in the first point cloud – claim 16 only} {as corresponding one or more query points for traversing – claims 2 and 9 only} a/the [compressed] octree representation {[of the second point cloud] – claims 2 and 16 only} to identify one or more nodes of the [compressed] octree representation that correspond to {points [of the second point cloud] that are nearest neighbor points of the one or more individual first points - claim 2/ a same area as one or more points included in the first point cloud – claim 9 / an area within the region that also corresponds to one or more points included in the first point cloud – claim 16} (Behley page 3625, section (II)(B), the octree is searched by a query point q in the three-dimensional point cloud space
R
3
and a radius including the point q, to find (identify) an overlapping leaf octant (one or more nodes) with points inside the search ball (correspond to an area within the region), and page 3626, section III, teaching traverse the octree until reaching a leaf octant and then evaluating each point inside the leaf octant, where page 3625, section I teaches that the octree is a sparing representation of (correspondence to) a three-dimensional point cloud);
Behley does not explicitly teach, but Fu teaches:
determining a nearest neighbor correspondence between points of a first point cloud and one or more individual second points of a second point cloud corresponding to at least one second sensor scan of the region (Fu page 5617, section 1.2, a Kinect is used to grab 16 (thus at least a first and second sensor scan) three-dimensional point clouds of an object, and page 5619, registration of two point clouds (first and second point cloud) including an alignment that determines the k-nearest neighbors to individual points n1, n2, … nk);
query points for a compressed octree representation of the second point cloud … one or more nodes of the compressed octree representation that correspond to points of the second point cloud (Fu pages 5618–5619, and fig. 2, Point Cloud Compression Based on Octree and Precise Registration Using Improved ICP sections, compressed point clouds based on octree structures are first determined, then in an Improved ICP registration, for a given point pi in a first point cloud (query points) a point xi in the second point cloud (compressed octree according to fig. 2 which shows the ICP registration downstream of the compression based on octree step), is identified that corresponds to the query point and corresponds to a node based on the octree structure).
Behley does not explicitly teach, but Egger teaches:
{claim 2 only - determining a location of a machine within the region based at least on the correspondence (Egger page 3430, and Abstract, localizing (determining a location) for a vehicle (machine) within a map (the region) by obtaining the closest map nodes to map features determined by LIDAR sensing (the correspondence));} and
performing one or more control operations with respect to the machine based at least on the {location – claim 2 / correspondence – claims 9 and 16} (Egger page 3430, and Abstract, waypoint navigation in response to localization determination, the waypoint navigation involving moving a vehicle (performing one or more control operations) along predefined routes within a certain area).
Therefore, taking the teachings of Behley as modified by Fu and Egger together as a whole, it would have been obvious to a person having ordinary skill in the art (herein “PHOSITA”) before the effective filing date of the claimed invention to have modified the octree and traversal of Behley to be from two separate scanned point clouds as discussed in Fu, at least because doing so would reduce computation time in referencing point cloud structures. See Fu page 5621.
Further, taking the teachings of Behley as modified by Fu and Egger together as a whole, it would have been obvious to a PHOSITA before the effective filing date of the claimed invention to have modified the octree of Behley to be compressed, and the result of the query searching of the octree of Behley to be the localization and thereafter waypoint navigation as disclosed in Egger at least because doing so would provide autonomous driving capabilities with high accuracy in navigation. See Egger Abstract.
Regarding claims 3, 11 and 17, with claim 3 as exemplary, and with deficiencies of Behley noted in square brackets, Behley teaches wherein the traversing of the [compressed] octree representation is based at least on a search space that {corresponds to the area and that – claims 11 and 17} is defined based at least on {the one or more query points – claims 3 and 11 / an individual first point included in the first point cloud – claim 17} and a search range around {one or more point locations – claims 3 and 11 / a location – claim 17} {in the region – claims 3 and 17} that correspond(s) to the {one or more query points – claims 3 and 11 / first point – claim 17} (Behley page 3625, section (II)(B), the octree is traversed using by a query point q (first point) in the three-dimensional point cloud space
R
3
and a radius (search range) including the point q defining a search ball S(q,r) (search space), to find (identify) an overlapping leaf octant (one or more nodes) with points inside the search ball (correspond to an area within the region)).
As noted above in the rejection for claim 2, while Behley discloses the octree to be “a sparing representation” of a point cloud, Behley does not explicitly teach the octree to be a compressed octree. Egger teaches a compressed octree (Egger pages 3432–3433, sections IV(A) and IV(B), in generating a PoseMap generated by propagating surfels through an octree, and then filtering is performed to result in a sparse map (octree), where page 3434 section V teaches that the sparse map has a size of 9.4MB versus the point cloud having 5GB, thus the sparse map (octree) is smaller and compressed).
Regarding claims 4, 12 and 18, with deficiencies of Behley noted in square brackets, Behley teaches wherein the traversing of the [compressed] octree representation includes selecting a particular node of the [compressed] octree representation and performing one or more traversing operations with respect to the particular node based at least on the search space (Behley page 3626 section III, in the leaf-based octree, the tree is traversed until a leaf octant (particular node) is reached, and then, each point inside the leaf octant is tested for inclusion (traversing operation) inside the search ball S(q, r) (based on the search space)).
As noted above in the rejection for claim 2, while Behley discloses the octree to be “a sparing representation” of a point cloud, Behley does not explicitly teach the octree to be a compressed octree. Egger teaches a compressed octree (Egger pages 3432–3433, sections IV(A) and IV(B), in generating a PoseMap generated by propagating surfels through an octree, and then filtering is performed to result in a sparse map (octree), where page 3434 section V teaches that the sparse map has a size of 9.4MB versus the point cloud having 5GB, thus the sparse map (octree) is smaller and compressed).
Regarding claims 5, 13 and 19, with claim 5 as representative, Behley teaches wherein the one or more traversing operations include one or more of: marking the particular node as corresponding to an area within the region that corresponds to the one or more query points responsive to the particular node being determined to be a leaf node and responsive to a determination that one or more coordinates associated with a current node correspond to the search space (Behley page 3626 section III, in the leaf-based octree, the tree is traversed until a leaf octant (leaf node) is reached, and then, each point inside the leaf octant is tested for inclusion (traversing operation) inside the search ball S(q, r) (the search space), where traversing stops once an octant is found that is completely inside of S(q, r));
responsive to a determination that the particular node is not a leaf node and responsive to the determination that one or more coordinates associated with the particular node correspond to the search space, identifying a child node of the particular node and performing the one or more traversing operations with respect to the identified child node in which the identified child node is selected as the next particular node used in the one or more traversing operations; or responsive to determining that no coordinates associated with the particular node correspond to the search space, identifying a sibling node of the particular node and performing the one or more traversing operations with respect to the identified sibling node in which the identified sibling node is selected as the next particular node used in the one or more traversing operations (given that the above limitations are recited with the alternative “or” thus only requiring one of these limitations to be met to meet the broadest reasonable interpretation of the claim, nonetheless, in addition to the marking limitation as provided above, Behley further teaches the first responsive limitation regarding child nodes on page 3626, section III, algorithm 1, as shown in the algorithm reproduced below for convenience:
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a “for loop” at line 11 is provided, where the for loop is not executed if the octant is a leaf octant (leaf node) since leaf octants have their own “for loop” at line 6, returning at line 9 and thus not executing the for loop at line 11 – therefore the for loop in line 11 is for the situation where it is determined that the particular node is not a leaf node, and within the for loop routine in line 11, an evaluation is made for each child octant of O, thus if there are child nodes, they are identified in line 11, and the for loop executes including further traversal operations as in line 12 considering whether the child octant C of O has overlap with the search space S(q , r), and if so, that child octant (node) has a radiusNeighbors algorithm executed upon it (is selected as the next particular node used in the one or more traversing operations)).
Regarding claims 6, 14 and 20, Behley teaches wherein no traversing operations are performed for any child node of the particular node responsive to determining that no coordinates associated with the particular node correspond to the search space (Behley page 3626, section III, algorithm 1, in the for loop at line 11 which processes child nodes of the particular node, the radiusNeighbors routine (traversing operations) are not performed when the coordinates of the child octant C do not overlap (no coordinates associated) with the search space S(q, r)).
Regarding claims 8, 15 and 21, while Behley teaches traversing the octree representation as set forth above in the rejection of claims 2, 9 and 16, Behley does not explicitly teach the octree to be a compressed octree, or that the traversing is performed without decompressing the compressed octree representation. Egger teaches the compressed octree representation is performed (Egger pages 3432–3433, sections IV(A) and IV(B), in generating a PoseMap generated by propagating surfels through an octree, and then filtering is performed to result in a sparse map (octree), where page 3434 section V teaches that the sparse map has a size of 9.4MB versus the point cloud having 5GB, thus the sparse map (octree) is smaller and compressed) without decompressing the compressed octree representation (Egger page 3437, section E, the extracted PoseMap is used to localize, detailed further on page 3433 section C, Localization, and this process is not disclosed as including a decompression of the PoseMap, rather the traversal is disclosed as being simple and fast involving only the closest two submaps to a current queried position).
Therefore, taking the teachings of Behley as modified by Fu and Egger together as a whole, it would have been obvious to a PHOSITA before the effective filing date of the claimed invention to have modified the traversing of the octree of Behley to not involve decompressing the octree as disclosed in Egger at least because doing so would reduce computational costs and allow taking advantage of the full range of the position sensors used. See Egger page 3433, section C.
Regarding claim 10, Behley does not explicitly teach, but Egger teaches wherein the performing of the one or more control operations with respect to the machine based at least on the correspondence is based at least on a location of the machine that is determined based at least on the correspondence (Egger page 3430, and Abstract, localizing (location that is determined) for a vehicle (machine) within a map by obtaining the closest map nodes to map features determined by LIDAR sensing (the correspondence) the waypoint navigation in response to localization determination, the waypoint navigation involving moving a vehicle (performing one or more control operations) along predefined routes within a certain area).
Therefore, taking the teachings of Behley as modified by Fu and Egger together as a whole, it would have been obvious to a PHOSITA before the effective filing date of the claimed invention to have modified Behley to have the result of the query searching of the octree of Behley to be the localization and thereafter waypoint navigation as disclosed in Egger at least because doing so would provide autonomous driving capabilities with high accuracy in navigation. See Egger Abstract.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Behley in view of Fu in view of Egger, as set forth above regarding the independent claims from which this claim depends, further in view of Sugio et al., US Patent Application Publication No. US 2021/0004993 A1 (herein “Sugio”).
Regarding claim 7, Behley as modified by Fu and Egger does not explicitly teach, but Sugio teaches wherein the identifying of the sibling node of the particular node (Sugio ¶¶ 1018, 1108–1109 and 1296, and figs. 136–137, determining neighboring nodes of the current node having the same parent) is based at least on a sibling link corresponding to the particular node, the sibling link storing an index of the sibling node, the index identifying the sibling node in a linear array (Sugio ¶¶ 1356 and 1361, the geometry information calculator stores occupancy information to which the current node belongs, the occupancy node is a neighboring node belongs to a parent of an current node, the neighbor node information is stored in a list or an index).
Therefore, taking the teachings of Behley as modified by Fu and Egger above, and Sugio together as a whole, it would have been obvious to a PHOSITA before the effective filing date of the claimed invention to have modified the identifying of nodes in Behley to include sibling nodes based on linking indices in a list as disclosed in Sugio at least because doing so would improve coding efficiency of 3D data. See Sugio ¶ 11.
Conclusion
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MICHELLE M. KOETH
Primary Examiner
Art Unit 2671
/MICHELLE M KOETH/Primary Examiner, Art Unit 2671
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