Prosecution Insights
Last updated: July 17, 2026
Application No. 18/630,640

HYBRID NEURAL NETWORK-BASED OBJECT TRACKING WITH BOUNDING BOX STATE ESTIMATION FROM A SPARSE RADAR DETECTION DISTRIBUTION

Non-Final OA §102§103§112
Filed
Apr 09, 2024
Examiner
MOORE, WHITNEY
Art Unit
3646
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Aptiv Technologies AG
OA Round
1 (Non-Final)
88%
Grant Probability
Favorable
1-2
OA Rounds
0m
Est. Remaining
98%
With Interview

Examiner Intelligence

Grants 88% — above average
88%
Career Allowance Rate
1021 granted / 1157 resolved
+36.2% vs TC avg
Moderate +10% lift
Without
With
+9.9%
Interview Lift
resolved cases with interview
Fast prosecutor
2y 2m
Avg Prosecution
30 currently pending
Career history
1190
Total Applications
across all art units

Statute-Specific Performance

§101
2.6%
-37.4% vs TC avg
§103
75.5%
+35.5% vs TC avg
§102
10.6%
-29.4% vs TC avg
§112
6.9%
-33.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1157 resolved cases

Office Action

§102 §103 §112
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 . Information Disclosure Statement This office acknowledges receipt of the following item(s) from the applicant: Information Disclosure Statement(s) (IDS) filed on 09 April 2024 and 02 May 2025. The references have been considered. Claim Interpretation The following is a quotation of 35 U.S.C. 112(f): (f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph: An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked. As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph: (A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function; (B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and (C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function. Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function. Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function. Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: the plurality of modules in claims 1, 3-13, 15, 17, 19 and 20. Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. Claim Rejections - 35 USC § 112 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Referring to Claims 1 and 15, the limitation “…the deep neural network model configured to generate an estimate state of a bounding box…” is not clear, as it is not clear if the bounding box is also generated or created by the model or if they bounding box is created in a different unclaimed step. As the estimate step is of a bounding box it reads as if the bounding box is created prior to estimate step and is not created by the model. However, it is not clear how to interpret this limitation and clarification is required. Claims 2-14 and 16-20 are dependent on Claims 1 and 15 and are subject to the same rejection. Claim Rejections - 35 USC § 102 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. Claim(s) 1, 2 and 13-16 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Timm et al. (Timm, DE102020209535 machine translation). Referring to Claim 1, Timm teaches a hybrid object tracking module (Fig. 1 #12 and 34; [0002] and [0019]) comprising a radar detection module configured to receive a sparse radar detection distribution including radar detections based on a radar signal emitted from a host vehicle (Fig. 1 #14; [0015-0016], an object parameter determining module configured to generate an object track including centroid information for a detected object relative to the host vehicle ([0019]), and a plurality of modules implementing a deep neural network model and comprising a plurality of neural networks, the deep neural network model configured to generate an estimate state of a bounding box and a confidence level of the estimated state of the bounding box based on the radar detections and the centroid information (Fig. 3 and [0020-0024]); and a driver assistance module configured to perform driver assistance operations based on the estimated state of the bounding box and the confidence level; Fig. 1 #40; [0021]. Referring to Claims 2 and 16, Timm teaches wherein: the sparse radar detection distribution includes only peak radar detections; and the plurality of modules are configured to generate the estimated state of the bounding box and the confidence level based on the peak radar detections; [0010]. Referring to Claim 13, Timm teaches the driver assistance system of claim 1; a steering system (Fig. 1 #22; [0015]); a braking system (Fig. 1 #20; [0015]); and a propulsion system (Fig. 1 #18; [0015]), the driver assistance module controlling operations of at least one of the steering system, the braking system, and the propulsion system based on the estimated state of the bounding box and the confidence level; [0014-0017] and citations of claim 1 above. Referring to Claim 14, Timm teaches the driver assistance system of claim 1; and a radar sensor configured to generate the radar signal and generate the radar detections based on reflection of the radar signal off at least one of the detected object and one or more other objects; See citations of Claim 1. Referring to Claim 15, Timm teaches receiving reflections of a radar signal emitted from a host vehicle; generating a sparse radar detection distribution including radar detections based on the received reflections of the radar signal, generating an object track including centroid information for a detected object relative to the host vehicle; implementing via a plurality of modules, a deep neural network model comprising a plurality of neural networks, the deep neural network model configured to generate an estimate state of a bounding box and a confidence level of the estimated state of the bounding box based on the radar detections and the centroid information; and performing driver assistance operations based on the estimated state of the bounding box and the confidence level; see citations of Claim 1 as this is the corresponding method. Claim Rejections - 35 USC § 103 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. Claim(s) 3, 4, 12, 17 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Timmin view of Koivisto et al. (Koivisto, US PGPub 2019/0258878). Referring to Claims 3 and 17, Timm teaches the limitations of Claims 1 and 15, but does not explicitly disclose nor limit wherein: the plurality of modules comprise a recurrent track feature abstractor module configured to generate hidden features based on the object track, and an object centroid head module configured to estimate a position and a velocity of a centrode of the bounding box; and the estimated state of the bounding box comprises the estimated position and the estimated velocity. However, Timm teaches a neural network made of a plurality of modules that is used for tracking an object, and estimate position and velocity of the object and contains hidden layers; See Fig. 3 and associated text as well as [0034-0050] which teaches an example neural network. Nevertheless as it is not explicit, Koivisto teaches a neural network wherein: the plurality of modules comprise a recurrent track feature abstractor module configured to generate hidden features based on the object track, and an object centroid head module configured to estimate a position and a velocity of a centrode of the bounding box; and the estimated state of the bounding box comprises the estimated position and the estimated velocity; Fig. 1B [0041], [0093], [0110-0111] and [0125]. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Timm with the neural network modules and features as taught by Koivisto as is well known in the art applying a known technique to a known device (method, or product) ready for improvement to yield predictable results such improving the accuracy of final detected objects. Referring to Claims 4 and 18, Timm as modified by Koivisto teach wherein the object centroid head module comprises: a first concatenator configured to receive and concatenate a plurality of inputs including the hidden features ([0104] and [0111]); fully connected layers ([0085]) and a rectified linear unit ([0086]) configured to receive an output of the first concatenator; a fully connected layer configured to receive an output of the fully connected layers and the rectified linear unit; and a summer configured to add an absolute position of a centroid of the object track to an output of the fully connected layer to provide the estimated position of the bounding box; See at least Fig. 3 of Koivisto and associated text.. Referring to Claim 12, Timm as modified by Koivisto teaches wherein the hybrid object tracking module further comprises: a ground truth comparison module configured, during at least one of calibration and training of the deep neural network model, to compare an output of a first one or more of the plurality of modules to a ground truth and generate an error value based on a result of the comparison; and a loss function module configured to adjust operation of a second one or more of the plurality of modules based on the error value; “Examples of Ground Truth Generation for Object Detection” section of Koivisto. Allowable Subject Matter Claims 5-11, 19 and 20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to WHITNEY T MOORE whose telephone number is (571)270-3338. The examiner can normally be reached Monday-Friday from 7am-4pm. 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, Jack Keith can be reached at (571) 272-6878. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /WHITNEY MOORE/Primary Examiner, Art Unit 3646
Read full office action

Prosecution Timeline

Apr 09, 2024
Application Filed
May 29, 2026
Non-Final Rejection mailed — §102, §103, §112 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12681129
METHOD AND APPARATUS THAT USES RADIO TRANSMISSIONS FOR SURFACE MAPPING
2y 9m to grant Granted Jul 14, 2026
Patent 12681121
ANGLE AMBIGUITY MITIGATION FOR INTERFEROMETRY
2y 8m to grant Granted Jul 14, 2026
Patent 12676409
INTEGRATED CIRCUIT AND SYSTEM WITH TRACKING
3y 2m to grant Granted Jul 07, 2026
Patent 12674880
System, Device, And Method For Estimating Position Information with Respect To At Least One Target Node
3y 2m to grant Granted Jul 07, 2026
Patent 12670748
APPARATUS FOR DRIVER ASSISTANCE AND METHOD OF CONTROLLING THE SAME
3y 0m to grant Granted Jun 30, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

Strategy Recommendation AI-generated — please review before filing

Get a prosecution strategy drawn from examiner precedents, rejection analysis, and claim mapping.
Typically takes 5-10 seconds — AI-generated, attorney review required before filing

Prosecution Projections

1-2
Expected OA Rounds
88%
Grant Probability
98%
With Interview (+9.9%)
2y 2m (~0m remaining)
Median Time to Grant
Low
PTA Risk
Based on 1157 resolved cases by this examiner. Grant probability derived from career allowance rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month