Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Status of the Claims
This action is in response to the applicant’s filing on March 26, 2025. Claims 1-20 are pending.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(B) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 1 recites the limitation “the environment”. There is insufficient antecedent basis for this limitation in the claim.
Claims 2-11 are rejected for incorporation of the errors of the base claim by dependency.
Claim 7 recites the limitation “the current object track”. There is insufficient antecedent basis for this limitation in the claim.
Claim 12 recites the limitation “the autonomous vehicle”. There is insufficient antecedent basis for this limitation in the claim.
Claims 13-20 are rejected for incorporation of the errors of the base claim by dependency.
Claim 16 recites the limitation “the visibility representation”. There is insufficient antecedent basis for this limitation in the claims. Claim 16 is dependent on claim 12, which introduced “an environmental visibility representation” and made secondary reference to “the environmental visibility representation”.
The term “classically programmed object detector” in claim 20 is a relative term which renders the claim indefinite. The term “classically programmed object detector” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. In the Specification, at [0062], there is a mention of “classical approaches” as an example of non-learned methods, also including rule-based methods, expert systems, heuristic approaches, deterministic approaches, hand-crafted algorithms, analytic methods, and/or other suitable techniques. It is unclear, and therefore indefinite, which of these are defined as “classical approaches” or “classically programmed object detector”. No definition of the term is provided or understood in the relevant art.
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 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 1-5, 7-15, 18 and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Pang, et al. U.S. Patent Application Publication 2023/0282000 A1.
As to claim 1, Pang et al. discloses a method comprising:
determining a set of measurements with a vehicle sensor suite (0016, 0029);
determining an environmental visibility map based on the set of measurements (Figure 9, 0049);
using the environmental visibility map and a prior object track, estimating a probability of detection of an object in the environment, wherein the object is associated with the prior object track (0015, 0018);
based on the set of measurements, determining an object detection (0015);
updating the prior object track to yield a current object track (0023);
based on the object detection and the probability of detection of the object,
determining a probability of existence of the current object track (0018); and
controlling a vehicle based on the current object track and the probability of existence (0036, 0039).
As to claim 2, Pang et al. discloses the method of claim 1, and further discloses wherein determining the probability of existence comprises using Poisson Multi-Bernoulli Mixturing (PMBM) (0015, 0017, 0018).
As to claim 3, Pang et al. discloses the method of claim 1, and further discloses wherein estimating the probability of detection of the object comprises:
predicting a position of the object using a trajectory of the current object track (0016, 0017); and
sampling the environmental visibility map using the predicted position of the object (0015, 0021).
As to claim 4, Pang et al. discloses the method of claim 1, and further discloses wherein the visibility map is a binary map (0058), wherein the probability of detection is non-binary (0015, 0018).
As to claim 5, Pang et al. discloses the method of claim 4, and further discloses wherein determining the probability of detection comprises sampling multiple values within a boundary hull associated with the current object track (0018, 0019).
As to claim 7, Pang et al. discloses the method of claim 1, and further discloses further comprising:
determining a next set of measurements with the vehicle sensor suite (0016, 0029);
determining a next environmental visibility map based on the next set of measurements (Figure 9, 0049);
determining that the object is not detected in the next set of measurements (0015, 0018);
determining a next probability of detection of the object using the next environmental visibility map and the current object track (0018); and
responsive to the object not being detected, updating the probability of existence of the current object track based on the next probability of detection of the object (0023).
As to claim 8, Pang et al. discloses the method of claim 1, and further discloses wherein updating the probability of existence comprises applying a dynamically updating a prior probability of existence (0018).
As to claim 9, Pang et al. discloses the method of claim 1, and further discloses wherein determining the environmental visibility map comprises ray tracing from Lidar scans of the set of measurements (0035, 0041).
As to claim 10, Pang et al. discloses the method of claim 1, and further discloses wherein the environmental visibility map represents visibility from a plurality of sensors of the vehicle sensor suite and is determined based on predetermined relative positions of the plurality of sensors (Figure 9, 0015, 0049).
As to claim 11, Pang et al. discloses the method of claim 1, and further discloses wherein measurements used to determine the environmental visibility map comprise lidar measurements and measurements used to detect the object comprise camera measurements (0016-0017).
As to claim 12, Pang et al. discloses a method comprising:
determining a set of measurements with a vehicle sensor suite (0016, 0029);
determining an environmental visibility representation based on the set of measurements (Figure 9, 0049);
using the environmental visibility representation, estimating a probability of detection of an object associated with an object track (0015, 0018);
determining that the object is undetected within the set of measurements (0015);
responsive to the determination of the object being undetected within the set of measurements, determining a probability of existence for the object track based on the probability of detection of the object (0018); and
controlling the autonomous vehicle based on the object track and the probability of existence (0036, 0039).
As to claim 13, Pang et al. discloses the method of claim 12, wherein determining the probability of existence comprises applying a dynamic update to a prior probability of existence (0018).
As to claim 14, Pang et al. discloses the method of claim 12, and further discloses wherein the object is associated with multiple distinct object tracks (0016, 0018).
As to claim 15, Pang et al. discloses the method of claim 12, and further discloses wherein measurements used to determine the environmental visibility representation are in a different modality from measurements used to detect the object (0016-0017).
As to claim 18, Pang et al. discloses the method of claim 12, and further discloses wherein the environmental visibility representation comprises binary values, and the probability of detection is non-binary (0015, 0018).
As to claim 20, Pang et al. discloses the method of claim 12, and further discloses wherein determining an environmental visibility representation based on the set of measurements comprises: detecting objects using a classically programmed object detector (0020).
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 6, 16-17 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Pang, et al. U.S. Patent Application Publication 2023/0282000 A1 in view of Ting et al., U.S. Patent 12,455,358 B2 (2025).
As to claim 6, Pang et al. discloses the method of claim 1. Pang et al. does not disclose a semantic classification, as claimed.
Ting et al. discloses further comprising normalizing a semantic classification of the current object track based on the probability of existence, and wherein controlling the vehicle comprises using the semantic classification (Column 3, Lines 1-16, Column 16, Lines 4-37).
It would have been obvious to one having ordinary skill in the relevant art before the effective filing date of the claimed invention to combine the method of claim 1, as disclosed by Pang et al., with the use of semantic classification, as claimed, as disclosed by Ting et al., with a reasonable expectation of success, allowing for the use of a common technique to sort the relevant sensor information.
As to claim 16, Pang et al. discloses the method of claim 12. Pang et al. does not disclose multiple index sampling, as claimed.
Ting et al. discloses wherein estimating the probability of detection of the object comprises sampling the visibility representation at multiple indexes (Column 3, Lines 1-16).
It would have been obvious to one having ordinary skill in the relevant art before the effective filing date of the claimed invention to combine the method of claim 12, as disclosed by Pang et al., with the use of multiple index sampling, as claimed, as claimed, as disclosed by Ting et al., with a reasonable expectation of success, allowing for multiple types of data. The Specification does not describe any type of index.
As to claim 17, Pang et al., as modified by Ting et al., discloses the method of claim 16. Pang et al. does not disclose a classification, as claimed. Ting et al. further discloses wherein the multiple indexes are based on a classification of the object (Column 3, Lines 1-16, Column 16, Lines 4-37).
It would have been obvious to one having ordinary skill in the relevant art before the effective filing date of the claimed invention to combine the method of claim 16, as disclosed by Pang et al., as modified by Ting et al., with the use of classification, as claimed, as disclosed by Ting et al., with a reasonable expectation of success, allowing for the use of a common technique to sort the relevant sensor information.
As to claim 19, Pang et al. discloses the method of claim 12. Pang et al. does not disclose a normalizing a prior classification, as claimed.
Ting et al. discloses , and further discloses further comprising normalizing a prior classification of the object track based on the probability of existence (Column 3, Lines 1-16, Column 16, Lines 4-37).
It would have been obvious to one having ordinary skill in the relevant art before the effective filing date of the claimed invention to combine the method of claim 12, as disclosed by Pang et al., with the use of normalizing a prior classification, as claimed, as disclosed by Ting et al., with a reasonable expectation of success, allowing for the use of a common technique to sort the relevant sensor information.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The publication of the present application is cited. Issued patents from the IDS citations are cited. Tominaga et al. discloses a related technology.
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MICHAEL BERNS
Primary Examiner
Art Unit 3667
/MICHAEL A BERNS/Primary Examiner, Art Unit 3667
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