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 Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 submission filed on 09/11/2026 has been entered.
Response to Arguments
Applicant's arguments filed 09/11/2026 have been fully considered but they are not persuasive. Regarding the claim amendment, the claim amendments fail to amount to significantly more because they are generally recited and fail to convey improvements to the functioning of a computer. The applicant highlights the limitation “controlling autonomous driving of the vehicle, based on a determined shape flag of an object.” This limitation with respect to MPEP 2106.05(I)(A)(ii) simply append well-understood, routine, conventional activities well known in the industry, specified at a high level of generality, to the judicial exception (please reference (Improvements to Computer Functionality, Example III of the courts indicating may NOT be sufficient to show improvement (MPEP 2106.05(a)(I))). It is for this reason that the examiner maintains the 101 rejection.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefore, subject to the conditions and requirements of this title.
Claims 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Specifically, representative Claim 1 recites:
A method for controlling a vehicle, the method comprising:
obtaining, by a LiDAR sensor mounted on the vehicle, a plurality of layers of LiDAR points for an object around the vehicle, wherein each of the plurality of layers includes LiDAR point data of the object at its corresponding position on a vertical axis;
determining, by a processor mounted in the vehicle, a shape flag for each layer of the plurality of layers by use of at least a part of LiDAR points thereon according to a plurality of predetermined shape types;
calculating, by the processor, a confidence score for the shape flag determined for each layer of the plurality of layers by use of the at least part of LiDAR points;
determining, by the processor, a shape flag of the object by use of the shape flags determined for the plurality of layers and the confidence scores; and
controlling, by the processor, autonomous driving of the vehicle based on the determined shape flag of the object.
Claim 18 recites:
A vehicle including an object tracking device, the vehicle comprising: the object tracking device comprising: a LiDAR sensor configured to obtain first to Mth layers of LiDAR points for a target object around the vehicle, wherein M is an integer of 2 or greater, and wherein each of the first to Mth layers includes LiDAR point data of the target object at its corresponding position on a vertical axis; and a shape analysis unit configured to analyze a shape of the target, wherein the shape analysis unit comprises: a layer shape determination unit configured to determine a shape flag for each of the first to Mth layers by use of at least a part of LiDAR points thereon according to a plurality of predetermined shape types, and calculate a confidence score for the shape flag determined for each layer by use of the at least part of LiDAR points; and a target shape determination unit configured to determine a shape flag of the target object by use of the shape flags determined for the layers and the confidence scores; and a processor configured to control autonomous driving of the vehicle based on the determined shape flag of the object.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
Under Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (process).
Under Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim limitation, that covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) and mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion.
For example, steps of “calculate a confidence score for the shape flag determined for each layer by use of the at least part of LiDAR points;” are treated by the Examiner as belonging to mathematical concept grouping, while the steps of “ analyze a shape of the target, determine a shape flag for each of the first to Mth layers by use of at least a part of LiDAR points thereon according to a plurality of predetermined shape types; determine a shape flag of the target object by use of the shape flags determined for the layers and the confidence scores ” are treated as belonging to mental process grouping.
Similar limitations comprise the abstract ideas of Claims 18: steps of “calculating, by the processor, a confidence score for the shape flag determined for each layer of the plurality of layers by use of the at least part of LiDAR points;” are treated by the Examiner as belonging to mathematical concept grouping, while the steps of “determining, by a processor mounted in the vehicle, a shape flag for each layer of the plurality of layers by use of at least a part of LiDAR points thereon according to a plurality of predetermined shape types; determining, by the processor, a shape flag of the object by use of the shape flags determined for the plurality of layers and the confidence scores” are treated as belonging to mental process grouping. Next, under the Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application.
In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
The above claims comprise the following additional elements:
In Claim 18: object tracking device, shape analysis unit, layer shape determination unit, and target shape determination unit
The additional element of “obtaining a plurality of layers of LiDAR points for the object by use of the LiDAR; controlling, by the processor, the autonomous driving of the vehicle based on the determined shape flag of the object; obtain first to Mth layers of LiDAR points for a target object around the vehicle, wherein M is an integer of 2 or greater, and wherein each of the first to Mth layers includes LiDAR point data of the target object at its corresponding position on a vertical axis” represents a mere data gathering/outputting step and only adds an insignificant extra-solution activity to the judicial exception.
In conclusion, the above additional elements, considered individually and in combination with the other claim elements do not reflect an improvement to other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claims are directed at a judicial exception and require further analysis under the Step 2B.
However, the above claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B analysis).
The claims, therefore, are not patent eligible.
With regards to the dependent claims, claims 2-17 and 19 provide additional features/steps which are part of an expanded algorithm, so these limitations should be considered part of an expanded abstract idea of the independent claims.
Allowable Subject Matter
Claims 1-19 would be allowable if written overcome the 101 rejection set forth in this office action.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 1, Kaithakauzha teaches receiving three-dimensional (3D) point data and two-dimensional (2D) image data representing a field of view including a target object and an object volume prediction circuit configured to determine a predicted volume occupied by the target object within the 3D point data based on the 3D point data and the 2D image data [0005]. The object volume prediction circuit is further configured to analyze the 2D image data utilizing a plurality of neural network models, wherein the plurality of neural network models are configured to generate respective 2D bounding boxes for the target object based on the 2D image data [0006]. Kaithakauzha also teaches confidence score of the bounding box and whether its classification of the type of object is correct [0073].
Wu teaches L-shape fitting [0017] and the LiDAR sensor mounted to a vehicle [0007], but along with Kaithakauzha and all other references, fails to teach a method for controlling a vehicle, the method comprising: obtaining, by a LiDAR sensor mounted on the vehicle [0007]a plurality of layers of LiDAR points for an object around the vehicle, wherein each of the plurality of layers includes LiDAR point data of the object at its corresponding position on a vertical axis; determining, by a processor mounted in the vehicle, a shape flag for each layer of the plurality of layers by use of at least a part of LiDAR points thereon according to a plurality of predetermined shape types; calculating, by the processor, a confidence score for the shape flag determined for each layer of the plurality of layers by use of the at least part of LiDAR points; and determining, by the processor, a shape flag of the object by use of the shape flags determined for the plurality of layers and the confidence scores; and controlling, by the processor, the autonomous driving of the vehicle based on the determined shape flag of the object.
It is for this reason, Claim 1 and all of its dependencies would be allowed.
Regarding Claim 18, Kaithakauzha teaches receiving three-dimensional (3D) point data and two-dimensional (2D) image data representing a field of view including a target object and an object volume prediction circuit configured to determine a predicted volume occupied by the target object within the 3D point data based on the 3D point data and the 2D image data [0005]. The object volume prediction circuit is further configured to analyze the 2D image data utilizing a plurality of neural network models, wherein the plurality of neural network models are configured to generate respective 2D bounding boxes for the target object based on the 2D image data [0006]. Kaithakauzha also teaches confidence score of the bounding box and whether its classification of the type of object is correct [0073].
Wu teaches L-shape fitting [0017] and the LiDAR sensor mounted to a vehicle [0007], but along with Kaithakauzha and all other references fail to teach an object tracking device for controlling a vehicle, the object tracking device comprising: a LiDAR sensor configured to obtain first to Mth layers of LiDAR points for a target object around the vehicle, wherein M is an integer of 2 or greater, and wherein each of the first to Mth layers includes LiDAR point data of the target object at its corresponding position on a vertical axis; and a shape analysis unit configured to analyze a shape of the target, wherein the shape analysis unit comprises: a layer shape determination unit configured to determine a shape flag for each of the first to Mth layers by use of at least a part of LiDAR points thereon according to a plurality of predetermined shape types, and calculate a confidence score for the shape flag determined for each layer by use of the at least part of LiDAR points; and a target shape determination unit configured to determine a shape flag of the target object by use of the shape flags determined for the layers and the confidence scores; and a processor configured to control autonomous driving of the vehicle based on the determined shape flag of the object.
It is for this reason, Claim 18 and all of its dependencies, would be allowed.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J SINGLETARY whose telephone number is (571)272-4593. The examiner can normally be reached Monday-Friday 8:00am-5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Catherine Rastovski can be reached at 571-270-0349. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL J SINGLETARY/Examiner, Art Unit 2857
/ALEXANDER SATANOVSKY/Primary Examiner, Art Unit 2857
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