Prosecution Insights
Last updated: April 19, 2026
Application No. 17/972,382

LIGHT-BASED TIME-OF-FLIGHT SENSOR SIMULATION

Non-Final OA §102§103
Filed
Oct 24, 2022
Examiner
RATCLIFFE, LUKE D
Art Unit
3645
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
GM Cruise Holdings LLC
OA Round
1 (Non-Final)
87%
Grant Probability
Favorable
1-2
OA Rounds
2y 11m
To Grant
98%
With Interview

Examiner Intelligence

Grants 87% — above average
87%
Career Allow Rate
1476 granted / 1690 resolved
+35.3% vs TC avg
Moderate +10% lift
Without
With
+10.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
43 currently pending
Career history
1733
Total Applications
across all art units

Statute-Specific Performance

§101
2.3%
-37.7% vs TC avg
§103
50.2%
+10.2% vs TC avg
§102
26.3%
-13.7% vs TC avg
§112
13.6%
-26.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1690 resolved cases

Office Action

§102 §103
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 . 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. (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. Claim(s) 1, 8, and 17 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lindner, Marvin, et al. "Time-of-flight sensor calibration for accurate range sensing." Computer Vision and Image Understanding 114.12 (2010): 1318-1328. Referring to claim 1, 8, 17, and Lindner shows a computer-implemented method (see the method as shown in figure 5) comprising: obtaining data from a time-of-flight (TOF) sensor (see abstract also see figure 5 note the checkerboard images used to train the model that include depth and intensity) that received a reflected portion of a light signal from an object (see figure 1 note the signal modulation that is reflected off the 3D scene that is then received by the CMOS chip), wherein the data from the TOF sensor comprises a plurality of metrics (see figure 5 note the received checkerboard images), the plurality of metrics comprising a measure of noise and an amplitude of the reflected portion of the light signal (see the amplitude received in the images also see section 3.1 note the noise detected with the TOF system also see section 3.3 note systemic errors and distance information that is received); determining, based on the data from the TOF sensor, a signal to noise ratio (SNR) from the amplitude of the reflected portion of the light signal and the measure of noise (see figure 5 note the intensity calibration that is determined based on the presence of noise as well as the reflectivity and range to a target object as shown in section 5.3 note the reflectivity error also see figure 11); identifying a value of a simulated SNR to include in a set of simulation data based on an association between the data from the TOF sensor, the determined SNR, and the object (note the calibration that is performed in figure 5 that includes includes both intrinsic and extrinsic errors that is used to generate corrections for the calibrated depth images); and generating the set of simulation data that includes the value of the simulated SNR (see the calibration parameters that are produced in figure 5 and discussed in section 5.3 reflectivity related error adjustment). 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, 10, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lindner, Marvin, et al. "Time-of-flight sensor calibration for accurate range sensing." Computer Vision and Image Understanding 114.12 (2010): 1318-1328 in view of Grollius, Sara, et al. "Concept of an automotive LiDAR target simulator for direct time-of-flight LiDAR." IEEE Transactions on Intelligent Vehicles 8.1 (2021): 825-835. Referring to claims 3, 10, and 20 Linder shows the use of a calibration board to train a model for generating simulated SNR models for various scenarios however fails to show simulating operation of an AV in a simulated environment including a virtual object; and providing the set of simulation data for the virtual object to a perception layer of the AV. Grollius shows a similar device that includes simulating operation of an AV in a simulated environment including a virtual object; and providing the set of simulation data for the virtual object to a perception layer of the AV (see figure 2 that generates a virtual scenario that generates a simulated TOF as well as optical power, the optical power directly effecting the SNR of the return signal also see section III(A) representing the different reflections of the simulated target. It would have been obvious to include the simulated target scenario because this allows for different type of reflections representing real world situations that a TOF range would encounter in an AV environment. Claim(s) 6, 13, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lindner, Marvin, et al. "Time-of-flight sensor calibration for accurate range sensing." in view of Fang, Jin, et al. "Simulating LIDAR point cloud for autonomous driving using real-world scenes and traffic flows." arXiv preprint arXiv:1811.07112 1 (2018). Referring to claim 6, 13, and 16, while Lindner fails to show Fang shows further comprising training a computer model based on the set of simulation data, wherein the computer model simulates operation of an autonomous driving computer system (ADCS) associated with an autonomous vehicle (AV) (see abstract also see section C third paragraph where noise in the signal is simulated relative to determining distance to train an AV model of an ADCS. It would have been obvious to include the ADCS training system as shown by Fang because this is a common application for the specifics of the TOF SNR simulator as shown by Linder in a real world use item. Claim(s) 7 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lindner, Marvin, et al. "Time-of-flight sensor calibration for accurate range sensing." Referring to claim 7 and 14, while Linder fails to show a specific timing budget for execution of instructions one of ordinary skill in the art would realize that in a real world application that identifying a timing budget for executing instructions of a computer simulation of a virtual object located in a virtual environment; and organizing the set of simulation data such that a processor executing the instructions of the computer simulation performs the computer simulation within the timing budget would be obvious with any calibration. There is consistently thresholds that pertain to time and accuracy that are placed on any calibration system and this adds no new or unexpected results. The examiner is taking official notice in this statement and any number of references can be supplied that teach a time constraint on executing a simulation of an environment for calibration purposes. Allowable Subject Matter Claims 2, 4, 5, 9, 11, 12, 15, 18, and 19 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 LUKE D RATCLIFFE whose telephone number is (571)272-3110. The examiner can normally be reached M-F 9:00AM-5:00PM EST. 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, Isam Alsomiri can be reached at 571-272-6970. 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. /LUKE D RATCLIFFE/Primary Examiner, Art Unit 3645
Read full office action

Prosecution Timeline

Oct 24, 2022
Application Filed
Jan 30, 2026
Non-Final Rejection — §102, §103 (current)

Precedent Cases

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
87%
Grant Probability
98%
With Interview (+10.2%)
2y 11m
Median Time to Grant
Low
PTA Risk
Based on 1690 resolved cases by this examiner. Grant probability derived from career allow rate.

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