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 .
Election/Restrictions
Applicant's election with traverse of Group I, including claims 1-7, 16-20 in the reply filed on 08/06/2026 is acknowledged. The traversal is on the ground(s) that there is no serious burden. This is not found persuasive because of the following:
The inventions are independent or distinct, each from the other because they are independent and distinct as shown in their classification and separate searches.
Restriction for examination purposes as indicated is proper because all the inventions listed in this action are independent or distinct for the reasons given above and there would be a serious search and/or examination burden if restriction were not required because one or more of the following reasons apply:
Separate Search and Examination Burdens: Examining Claim 1 requires looking at how a vehicle uses obstacle and sensor data to predict paths. Examining Claim 8 requires searching and analyzing how datasets, training parameters, and loss functions (e.g., the error between prediction and transformed data) are structured. The prior art and search fields for these two are inherently different.
Independent Utility: The model trained in Claim 8 can theoretically be utilized for other purposes beyond spatial transformation and waypoint detection (e.g., energy optimization, classification), and the operational method in Claim 1 could theoretically use a model trained through other means.
Applicant argues that there is no serious burden in the restriction. The applicant that they demonstrate that there is no burden by arguing that:
“For example, a search of Group I, and in particular new dependent claim 21, should involve the related search of the structuring of the driving data set, the training of the neural network model, and the loss defined by the error between the prediction data and the waypoint transformed into the dual space, which the Office asserts will have to be searched for Group II. Likewise, the search of Group Il will involve a search of an inference, as a non-limiting example, use of the trained neural network to detect a next waypoint for the driving apparatus with respect to at least new dependent claim 22, which will be related to the Office's identified search of how a vehicle uses obstacle and sensor data to predict paths that the Office asserts will have to be searched for Group I. Moreover, Groups I and II as claimed share the same core features - the generation of safety constraint information from obstacle information, the generation of prediction data in a dual space using a neural network into which random noise is input, and the dual-space transformation of a waypoint - and several claims of Group II substantially mirror corresponding claims of Group I (compare, e.g., claims 2, 3, 4, and 5 with claims 9, 10, 12, and 14, respectively). A search directed to the features of the elected Group I claims would therefore necessarily encompass the field of search for the Group Il claims………………………”
The examiner respectfully disagrees. The applicant cannot use an amendment, wherein new unrelated and unsupported claims 21 and 22 are added, to shift prosecution to a different or unsupported invention after a restriction requirement. The specification as originally filed does not show that the inventor had possession of specifically the combination (Claim 1 + Claim 21/22). The examiner respectfully submits that there is no disclosed embodiment where these elements exist together in the original disclosure.
Therefore, the requirement is still deemed proper and is therefore made FINAL.
Claims 8-15 are withdrawn from further consideration pursuant to 37 CFR 1.142(b), as being drawn to a nonelected invention, there being no allowable generic or linking claim. Applicant timely traversed the restriction (election) requirement in the reply filed on 08/06/2026.
Newly submitted claims 21 and 22 are directed to an invention that is independent or distinct from the invention originally claimed for the following reasons:
a) the new claims are directed to a completely different invention with no disclosed connection to the original invention.
b ) the new claims recite essential features that are not present in the original claims, such that the inventions are not the same invention in different definitions
C ) there is no disclosed embodiment where these elements in the new claims exist together in the original disclosure.
Since applicant has received an action on the merits for the originally presented invention, this invention has been constructively elected by original presentation for prosecution on the merits.
Accordingly, claims 21 and 22 are withdrawn from consideration as being directed to a non-elected invention. See 37 CFR 1.142(b) and MPEP § 821.03.
To preserve a right to petition, the reply to this action must distinctly and specifically point out supposed errors in the restriction requirement. Otherwise, the election shall be treated as a final election without traverse. Traversal must be timely. Failure to timely traverse the requirement will result in the loss of right to petition under 37 CFR 1.144. If claims are subsequently added, applicant must indicate which of the subsequently added claims are readable upon the elected invention.
Should applicant traverse on the ground that the inventions are not patentably distinct, applicant should submit evidence or identify such evidence now of record showing the inventions to be obvious variants or clearly admit on the record that this is the case. In either instance, if the examiner finds one of the inventions unpatentable over the prior art, the evidence or admission may be used in a rejection under 35 U.S.C. 103 or pre-AIA 35 U.S.C. 103(a) of the other invention.
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 therefor, subject to the conditions and requirements of this title.
Claims 1-5, 7, 16, 17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
According to step 1 claim 1 is a process i.e. a method.
In addition, according to step 1 claim 17 is an apparatus.
According to step 2A, prong 1 the claimed invention is directed to a judicial exception (i.e., an abstract idea).
That is Claim(s) 1-5, 7, 16, 17 are directed to a processor implemented method.
Independent claim 1 recites:
--generating safety constraint information…….;
--generating prediction data…………;
--detecting a next waypoint for a …………...
These limitations are directed to implementing an intangible method within a processor using a mathematical algorithm and a neural network to perform mathematical operation on collected intangible data without significantly more.
According to step 2A, prong 2 the judicial exception is not integrated into a practical application. The claim has additional elements of a neural network, a driving apparatus, etc.
These simply apply the judicial exception to a particular technological environment by generally linking it to an intangible method. Accordingly, these additional elements do not integrate the abstract into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
According to step 2B, the claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because even though the claims recite a processor the processor is not used for moving the driving apparatus.
Accordingly, the claims recite additional elements that do not amount to significantly more than the judicial exception because the additional elements generally link the use of the judicial exception to merely detecting a next waypoint – see MPEP 2106.05(h)
Applicant may overcome the 101 rejection by reciting a computer or controller that controls the driving apparatus.
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 (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 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.
Claims 1-7, 16-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Vadivelu (US Pub 2025/0016534).
Regarding claim 1, Vadivelu discloses a processor-implemented method, the method comprising:
generating safety constraint information (information about a region or path or environment of safety for safe travel, or safe motion planning, or safe stopping of a vehicle; sec 0023, 0071, 0073) based on obstacle information obtained by sensing at a current waypoint (sec 0023, 0026-0032, 0060-0062);
generating prediction data in a dual space (X, Y, Z, etc space; (sec 0023, 0026-0032, 0060-0062, 0067-0073) from the safety constraint information and the current waypoint using a pre-trained neural network model (Neural Network, machine-learned detection and prediction model, etc; sec 0023,0033); and
detecting a next waypoint for a driving apparatus by performing spatial transformation on the prediction data (figs. 2, 3, 5-7; sec 0032, 0044, 0049-0059).
Regarding claim 2, Vadivelu discloses the method of claim 1, wherein the safety constraint information comprises one or more parameters that linearly constrain a range of the prediction data (figs. 2, 3, 5-7; sec 0032, 0044, 0059-0068).
Regarding claim 3, Vadivelu discloses the method of claim 2, wherein, the generating of the prediction data comprises determining based on the one or more parameters. a dual function that transforms the current waypoint into the dual space (sec 0059-0068, 0146-0149).
Regarding claim 4, Vadivelu discloses the method of claim 1, wherein the pre-trained neural network model includes a diffusion model, and the generating of the prediction data comprises inputting random noise into the pre- trained neural network model (sec 0026-0032, 0059-0068, 0146-0149).
Regarding claim 5, Vadivelu discloses the method of claim 1, wherein the generating of the safety constraint information comprises applying a predetermined algorithm to the obstacle information (sec 0026-0032, 0059-0068, 0146-0149).
Regarding claim 6, Vadivelu discloses the method of claim 1, further comprising: moving the driving apparatus to the next waypoint in response to the driving apparatus moving to the current waypoint; and repeating the moving process to reach a predetermined target location (sec 0026-0032, 0059-0068, 0146-0149).
Regarding claim 7, Vadivelu discloses the method of claim 1, wherein the current waypoint and the next waypoint are determined based on global positioning system (GPS; sec 0026).
Regarding claim 16, Vadivelu discloses a non-transitory computer-readable storage medium storing code that, when executed by one or more processors, configures the one or more processors to perform the method of claim 1 (figs. 2, 3, 5-7; sec 0026-0032).
Regarding claim 17, Vadivelu discloses the processor-implemented apparatus comprising:
one or more processors respectively comprising processing circuitry (figs. 2, 3, 5-7; sec 0026-0032); and
a memory storing code (figs. 2, 3, 5-7; sec 0026-0032), which upon execution by the one or more processors, configures the one or more processors to:
generating safety constraint information (information about a region or path or environment of safety for safe travel, or safe motion planning, or safe stopping of a vehicle; sec 0023, 0071, 0073) based on obstacle information obtained by sensing at a current waypoint (sec 0023, 0026-0032, 0060-0062);
generating prediction data in a dual space (X, Y, Z, etc space; sec 0023, 0026-0032, 0060-0062, 0067-0073) from the safety constraint information and the current waypoint using a pre-trained neural network model (Neural Network, machine-learned detection and prediction model, etc; sec 0023,0033); and
detecting a next waypoint for a driving apparatus by performing spatial transformation on the prediction data (figs. 2, 3, 5-7; sec 0032, 0044, 0049-0059).
Regarding claim 18, Vadivelu discloses the apparatus of claim 17, wherein the safety constraint information comprises one or more parameters that linearly constrain a range of the prediction data (figs. 2, 3, 5-7; sec 0032, 0044, 0059-0068); and
the one or more processors are further configured to:
move the driving apparatus to the next waypoint (sec 0026-0032, 0059-0068, 0146-0149); and
repeat the moving process to reach a predetermined target location (sec 0026-0032, 0059-0068, 0146-0149).
Regarding claim 19, Vadivelu discloses the apparatus of claim 18, wherein, for generating the prediction data, the one or more processors are configured to determine a dual function that transforms the current waypoint into the dual space based on the one or more parameters (sec 0059-0068, 0146-0149).
Regarding claim 20, Vadivelu discloses the apparatus of claim 17, wherein the pre-trained neural network model includes a diffusion model (sec 0059-0068, 0146-0149):
for generating the prediction data, the one or more processors are further configured to input random noise into the pre-trained neural network model (sec 0059-0068, 0146-0149); and
for generating the safety constraint information, the one or more processors are further configured to apply a predetermined algorithm to the obstacle information obtained (sec 0026-0032; 0059-0068, 0146-0149).
Conclusion
The prior art (US 20240414337 A1, US 20230060435 A1) made of record and not relied upon is considered pertinent to applicant's disclosure.
Communication
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RONNIE MANCHO whose telephone number is (571)272-6984. The examiner can normally be reached Mon-Thurs.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Adam Mott can be reached at 571 270 5376. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RONNIE M MANCHO/ Primary Examiner, Art Unit 3657
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