DETAILED ACTION
Non-Final Rejection
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
The information disclosure statement (IDS) submitted on 09/24/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Specification
The lengthy specification (more than 20 pages) has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant's cooperation is requested in correcting any errors of which applicant may become aware in the specification.
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.
Claim(s) 1-3, 7-14, and 17-20 are rejected under 35 U.S.C. 102“(a)(1)” as being anticipated by COSTEA (US 2023/0095410 A1).
Referring to Claim 1, COSTEA teaches one or more processors ([0063]) comprising:
processing circuitry ([0063]-[0065]) to:
determine, using one or more neural networks ([0052]; [0065]) and based at least on ultrasonic sensor data ([0057]; [0063]) and one or more other types of sensor data ([0057]), an output indicating one or more locations of one or more objects ([0064]); and
cause, based at least on the output ([0068]), a machine to perform one or more parking operations or one or more navigation operations ([0068]-[0069]).
Referring to Claim 2, COSTEA teaches the one or more processors of claim 1, wherein the processing circuitry ([0021]-[0027]; [0063]-[0065] is further to:
generate a representation associated with a sensory field of an ultrasonic sensor used to obtain the ultrasonic sensor data ([0021]-[0022]; [0057]),
wherein the output is determined using the one or more neural networks ([0022]-[0023]) and based at least on the representation ([0027]).
Referring to Claim 3, COSTEA teaches the one or more processors of claim 2, wherein the representation ([0021]) indicates at least one or more initial locations ([0022]-[0023]) associated with the one or more objects ([0022]-[0023]).
Referring to Claim 7, COSTEA teaches the one or more processors of claim 1, wherein the output includes a top-down image of an environment ([0021]-[0022]), the top-down image indicating the one or more locations ([0022]) of the one or more objects ([0022]-[0023]) at least partially surrounding the machine ([0019]; [0022]).
Referring to Claim 8, COSTEA teaches the one or more processors of claim 1, wherein the processing circuitry is further to:
generate, using the output indicating the one or more locations ([0025]-[0026]), a second output indicating an occupancy ([0022]; [0026]) associated with an environment at least partially surrounding the machine ([0021]-[0022]),
wherein the machine is caused to perform the one or more parking operations or the one or more navigation operations ([0023]; [0027]) based at least on the second output ([0021]-[0023]; [0027]; [0043]-[0046]).
Referring to Claim 9, COSTEA teaches the one or more processors of claim 1, wherein the one or more other types of sensor data include at least one of RADAR data, LiDAR data, or image data ([0056]-[0057]).
Referring to Claim 10, COSTEA teaches the one or more processors of claim 1, wherein the one or more processors are comprised in at least one of:
a control system for an autonomous or semi-autonomous machine ([0010]; [0068]-[0069]);
a perception system for an autonomous or semi-autonomous machine ([0063]-[0065]);
a system for performing simulation operations;
a system for performing digital twin operations;
a system for performing real-time streaming;
a system for generating or presenting virtual reality (VR) content;
a system for generating or presenting augmented reality (AR) content;
a system for generating or presenting mixed reality (MR) content;
a system for performing light transport simulation;
a system for performing collaborative content creation for 3D assets;
a system for performing deep learning operations;
a system implemented using an edge device;
a system implemented using a robot;
a system for performing conversational AI operations;
a system for generating synthetic data;
a system incorporating one or more virtual machines (VMs);
a system implemented at least partially in a data center (); or
a system implemented at least partially using cloud computing resources ().
Claim 11 is essentially the same as Claim 1 and refers to a method for the one or more processors of Claim 1; and further comprising, determine, using one or more neural networks (COSTEA’ [0052]; [0064]-[0065]) and based at least on a first sensor data obtained using one or more first sensors of a first sensor modality (COSTEA’ [0057]) and second sensor data obtained using one or more second sensors of a second sensor modality different from the first sensor modality (COSTEA’ [0057]).. Therefore Claim 11 is rejected for the same reasons as applied to Claim 1 above.
Claim 12 is essentially the same as Claim 2 and is rejected for the same reasons as applied to Claim 2 above.
Claim 13 is essentially the same as Claim 4 and is rejected for the same reasons as applied to Claim 4 above.
Referring to Claim 14, COSTEA teaches the method of claim 11, wherein the information includes at least one of:
a height map associated with the one or more objects;
an occupancy map associated with the one or more objects ([0021]-[0022]);
a distance map associated with the one or more objects; or
one or more indications of one or more locations associated with the one or more objects.
Claim 17 is essentially the same as Claim 9 and is rejected for the same reasons as applied to Claim 9 above.
Claim 18 is essentially the same as Claim 1 and refers to a system comprising: one or more central processing units (CPUs) (COSTEA’ [0073]); one or more graphics processing units (GPUs) (COSTEA’ [0073]); one or more hardware accelerators (COSTEA’ [0073]); one or more ultrasonic sensors (COSTEA’ [0057]); and one or more other sensors (COSTEA’ [0057]); wherein the system causes a machine to perform of Claim 1. Therefore Claim 18 is rejected for the same reasons as applied to Claim 1 above.
Referring to Claim 19, COSTEA teaches the system of claim 18, wherein one of: the ultrasonic data is associated with a same coordinate system as the other sensor data ([0048]-[0050]; [0057]);
or the ultrasonic data is associated with a different coordinate system than the other sensor data.
Claim 20 is essentially the same as Claim 10 and is rejected for the same reasons as applied to Claim 10 above.
Claim Rejections - 35 USC § 103
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 4-6 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over COSTEA as applied to claim 1 and 11 above, and further in view of BREED (US 2012/0209505 A1).
Referring to Claim 4, COSTEA teaches the one or more processors of claim 1, wherein the processing circuitry is further to:
generate, based at least on the ultrasonic sensor data, first information associated with the one or more objects ([0057]; [0063]-[0064]); and
generate, based at least on the one or more other types of sensor data, second information associated with the one or more objects ([0057]; [0063]-[0064]),
wherein the output is determined using the one or more neural networks ([0022]-[0023]; [0065]).
COSTEA doesn’t explicitly teach and based at least on the first information and the second information.
BREED teaches based at least on the first information and the second information ([0579])
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the one or more processors disclosed in COSTEA with at least on the first information and the second information taught in BREED with a reasonable expectation of success because it would have enables information from different sensors to be combined to obtain more information from the combined sensors that would be obtained by treading the sensor outputs independently, as taught by BREED ([0579])
Referring to Claim 5, COSTEA teaches the one or more processors of claim 1, wherein:
the ultrasonic sensor data is associated with a first coordinate system ([0057]) and the one or more other types of sensor data are associated with a second coordinate system ([0048]-[0050]);
the processing circuitry is further to generate, based at least on the one or more other types of sensor data, input data associated with the first coordinate system ([0049]-[0050]);
the output is determined using the one or more neural networks ([0052]).
COSTEA doesn’t explicitly teach and based at least on the ultrasonic data and the input data.
BREED teaches based at least on the ultrasonic data and the input data ([0579]).
Referring to Claim 6, COSTEA teaches the one or more processors of claim 1, wherein:
the ultrasonic sensor data is associated with a first coordinate system ([0057]) and the one or more other types of sensor data are associated with a second coordinate system [0047]-[0049];
the processing circuitry is further to generate, based at least on the ultrasonic data, input data associated with the second coordinate system ([0050]); and
the output is determined using the one or more neural networks ([0052]).
COSTEA doesn’t explicitly teach and based at least on the one or more other types of sensor data and the input data.
BREED teaches based at least on the one or more other types of sensor data and the input data ([0579]).
Claim 15 is essentially the same as Claim 5 and is rejected for the same reasons as applied to Claim 5 above.
Claim 16 is essentially the same as Claim 6 and is rejected for the same reasons as applied to Claim 6 above.
Examiner’s Note
Examiner has pointed out particular references contained in the prior art of record in the body of this action for the convenience of the Applicant. However, any citation to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968)). Applicant, in preparing the response, should consider fully the entire reference as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMIE M N'DURE whose telephone number is (571)272-6031. The examiner can normally be reached on 8AM-5:30PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Isam Alsomiri can be reached on 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 an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/AMIE M NDURE/Examiner, Art Unit 3645
/ABDALLAH ABULABAN/Primary Examiner, Art Unit 3645
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