DETAILED ACTION
Notice of AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
2. Applicant’s remarks received on 08/03/2026 with respect to the amended independent claims have been acknowledged and are moot in view of a new ground of rejection necessitated by the corresponding amendment. Currently claims 1-9 and 11-18 are rejected; and claim 10 is cancelled.
Response to Amendment
Claim Rejections - 35 USC § 103
3. 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 of this title, 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.
4. Claims 1-5, 8, 9, 11-14 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al (US Pub: 20230236323) and in further view of Vizzo et al (KISS-ICP: In Defense of Point-to-Point ICP– Simple, Accurate, and Robust Registration If Done the Right Way, 02/2023), Zhou et al (WO Pub: 2020168668), Sequeira et al (US Pub: 2018/0075643) and WO364’ (WO Pub: 2021025364).
Regarding claim 1 (currently amended), Lee et al teaches: A system for simultaneous localization and mapping (SLAM) [abstract], the system comprising: a light detection and ranging (Lidar) sensor configured to detect a feature point in front of a vehicle [p0045, p0080, fig. 1A]; and a controller configured to receive data on the feature point in front of the vehicle from the Lidar sensor [p0045, p0077-p0079], perform SLAM based on the feature point in the PCL [p0088-p0091, p0100-p0106], remove a feature point satisfying a removal condition from the PCL in response to an arrival of an object search cycle [p0101, p0102]; set the feature point received from the Lidar sensor and the feature point searched from the front image as a point cloud (PCL) [p0077-p0081 (integrated coordinate through point cloud merge)].
Lee et al does not explicitly define point removal condition based on distance. In the same field of endeavor, Vizzo et al teaches: wherein the feature point that satisfies the removal condition is a feature point whose distance to the vehicle is greater than a first set distance [page 1032: C. Step 3: p02]. Therefore, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of all to remove feature points based on distance to keep map size within boundary and reduce memory.
Vizzo et al adds new points from a newly acquired scan. In the same field of endeavor, Zhou further teaches camera detected feature points adding to current SLAM map: add a newly searched feature point after a previous object search cycle to the PCL [page 3: p09-p10]; and a camera configured to acquire a front image of the vehicle [page 9: p08]; receive the front image of the vehicle from the camera, search for the feature point from the front image [page 11: p02]. Therefore, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of all to add new feature points for providing updated environmental details.
Lee et al in view of Vizzo et al and Zhou does not specify removing a feature point that has been in PCL. In the same field of endeavor, Sequeira et al teaches: remove a feature point that i) has been a feature point in the PCL [p0102, p0104, p0112] and satisfying ii) satisfies a removal condition from the PCL [p0117], in response to an arrival of an object search cycle, wherein the feature point that satisfies the removal condition is a feature point whose distance to the vehicle is greater than a first set distance [p0139], and add a newly searched feature point [p0111, p0117].
And WO364’ teaches: set the feature point received from the Lidar sensor and the feature point searched from the front image as a point cloud (PCL), perform SLAM based on the feature point in the PCL [page 2: p02, p03; page 9: p05]; using the Lidar sensor and the front image after a previous object search cycle to the PCL [page 7: p06, page 8: p06, p07].
Therefore, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of all to delete previously store map point beyond certain distance as taught by Sequeira and determine newly search camera feature points as taught by WO364’ for improving accuracy.
Regarding claim 2 (original), the rationale applied to the rejection of claim 1 has been incorporated herein. Lee et al and Vizzo et al further teach: The system of claim 1, wherein the controller is further configured to maintain, in the PCL, a feature point that does not satisfy the removal condition [Lee: p0102, Vizzo: page 1032: C. Step 3: p02 (keep points not outside of max range)] .
Regarding claim 3 (original), the rationale applied to the rejection of claim 1 has been incorporated herein. Vizzo et al in view of Zhou et al further teaches: The system of claim 1, wherein the controller is configured to first remove the feature point that satisfies the removal condition from the PCL and then add the newly searched feature point to the PCL [Vizzo: page 1032: C. Step 3: p02; Zhou: page 3: p09-p10]. Therefore, given Vizzo in view of Zhou et al’s adding/removing feature points, the combined teaching would have made it obvious to add/remove feature points as part of same update cycle for better fit and bounded local map.
Regarding claim 4 (original), the rationale applied to the rejection of claim 1 has been incorporated herein. Vizzo et al and Zhou et al further teach: The system of claim 1, wherein the controller is further configured to: set the newly searched feature point after the previous object search cycle as a new point cloud (nPCL) [Vizzo: page 1031: III: p02, page 1032: B Step 2: p02, p03 (each received scan is treated as a new local point cloud.)]; determine whether the feature point in the nPCL is the same as the feature point in the PCL [Vizzo: page 1032: D: p01, page 1033: E: p03]; and add the corresponding feature point in the nPCL to the PCL in response to determining that the feature point in the nPCL is not the same as the feature point in the PCL [Vizzo: page 1032: C: p02, p1031: III: p02 (Adding new points for update); Zhou: page 6: p02].
Regarding claim 5 (original), the rationale applied to the rejection of clam 4 has been incorporated herein. Vizzo et al and Zhou et al further teach: The system of claim 4, wherein the controller is configured to determine that the feature point in the nPCL is not the same as the feature point in the PCL in response to determining that a minimum value of a distance between the feature point in the nPCL and the feature point in the PCL is greater than or equal to a second set distance [Vizzo: page 103: D: p01; Zhou: page 6: p02].
Regarding claim 8 (original), the rationale applied to the rejection of claim 4 has been incorporated herein. Lee et al further teaches: The system of claim 4, wherein the controller is further configured to remove noise in the nPCL through data clustering [p0102].
Claim 9 (currently amended) has been analyzed and rejected with regard to claim 1.
Regarding claim 11 (original), the rationale applied to the rejection of claim 9 has been incorporated herein. Claim 11 has been analyzed and rejected with regard to claim 2.
Regarding claim 12 (original), the rationale applied to the rejection of claim 9 has been incorporated herein. Claim 12 has been analyzed and rejected with regard to claim 4.
Regarding claims 13 and 14 (original), the rationale applied to the rejection of claim 12 has been incorporated herein. Claims 13 and 14 have been analyzed and rejected with regard to claim 5.
Regarding claim 18 (original), the rationale applied to the rejection of claim 12 has been incorporated herein. Claim 18 has been analyzed and rejected with regard to claim 8.
5. Claims 6, 7, and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al (US Pub: 20230236323), Vizzo et al (KISS-ICP: In Defense of Point-to-Point ICP– Simple, Accurate, and Robust Registration If Done the Right Way, 02/2023), and Zhou et al (WO Pub: 2020168668), Sequeira et al (US Pub: 2018/0075643) and WO364’ (WO Pub: 2021025364); and in further view of Qin et al (Geometric Transformer for Fast and Robust Point Cloud Registration, 03/12/2022).
Regarding claim 6 (original), the rationale applied to the rejection of claim 5 has been incorporated herein. Vizzo et al teaches initial nearest distance threshold as prescribed in claim 5. In the same field of endeavor, Qin et al teaches: The system of claim 5, wherein the controller is configured to: determine that a positional relationship between the feature point in the nPCL and the feature point other than the corresponding feature point in the PCL matches a positional relationship between the corresponding feature point in the PCL and the feature point other than the corresponding feature point in the PCL in response to determining that the minimum value of the distance between the feature point in the nPCL and the feature point in the PCL is less than the second set distance; and determine that the feature point in the nPCL is not the same as the feature point in the PCL in response to determining that the positional relationship between the feature point in the nPCL and the feature point other than the corresponding feature point in the PCL does not match the position relationship between the feature point in the PCL and the feature point other than the corresponding feature point in the PCL [abstract, fig. 1, page 4: p03 (geometric structure based on relationship among superpoints), page 2: Deep Robust Estimators (reject wrong matches based on positional inconsistency)].
Vizzo et al compares a current point cloud against an existing point cloud/local map. Zhou et al matches newly observed feature points to existing map points and add unmatched points. And Qin improves correspondence determination by matching positional relationship among points and rejects similar points with unmatched positional relationship. Therefore, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of all to accept feature points within distance threshold having matching positional relationship as matching points for improved reliability and accuracy.
Regarding claim 7 (original), the rationale applied to the rejection of claim 6 has been incorporated herein. Qin et al further teaches: The system of claim 6, wherein the controller is further configured to, in response to determining that the positional relationship between the feature point in the nPCL and the feature point other than the corresponding feature point in the PCL matches the positional relationship between the corresponding feature point in the PCL and the feature point other than the corresponding feature point in the PCL, determine that the corresponding feature point in the nPCL is the same as the corresponding feature point in the PCL [fig. 1, page 4: Superpoint matching; page 2: p03, page 5: p01, 3.3 Point Matching Module].
Regarding claims 15 and 16 (original), the rationale applied to the rejection of claim 13 has been incorporated herein. Claims 15 and 16 have been analyzed and rejected with regard to claim 6.
Regarding claim 17 (original), the rationale applied to the rejection of claim 15 has been incorporated herein. Claim 17 has been analyzed and rejected with regard to claim 7.
Conclusion
6. There is a new ground of rejection necessitated by the corresponding amendment 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 extension fee 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.
Contact
7. Any inquiry concerning this communication or earlier communications from the examiner should be directed to FAN ZHANG whose telephone number is (571)270-3751. The examiner can normally be reached on Mon-Fri 9:00-5:00.
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/Fan Zhang/
Patent Examiner, Art Unit 2682
Prosecution Insights