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 .
Application Status
This is the first Office action on the merits and is responsive to the papers filed on 06/24/2024. Claims 1-20 are currently pending and examined below. This action is NON-Final.
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.
Claim 1-20 are rejected under 35 U.S.C. 101 because
Step 1: Claims 1-20 are directed to method for obtaining a plurality of detection arcs; a system comprising: one or more processors comprising processing circuitry; a processing system comprising: one or more processors. The claims fall within at least one of the four categories of patent eligible subject matter because the claims recite a method for obtaining a plurality of detection arcs (a process), or a system comprising: one or more processors comprising processing circuitry (a manufacture). Step 1: Yes.
Step 2A – prong 1: Claims 1, 8, 15 recite the limitations, obtaining a plurality of detection arcs corresponding to detection of an object using a plurality of ultra sonic sensors, identifying the object based on the plurality of detection arcs. These limitations, as drafted, are a simple process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than “by a processor or a memory” nothing in the claims preclude the steps from practically being performed in the mind. For example, other than “by a microprocessor or a memory” language, the claims encompass a person looking at data collected and forming a simple judgement. The mere nominal recitation of a “by a processor or a memory” does not take the claim limitations out of the mental process grouping. Thus, claims 1, 8, and 15 are directed to mental process. Step 2A – Prong 1: Yes.
Step 2A- Prong 2: Claims 1, 8, and 15 recite an element of a processor or a
memory that is used to collecting data from a plurality of sensors. The processor or memory is recited at a high level of generality, therefore, acting as a generic computer to perform the abstract idea. The microprocessor or memory is claimed generically and is operating in its ordinary capacity and does not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claims are more than mere instructions to apply the exception using the microprocessor or memory. Additionally, the claims recite collecting data from a plurality of sensors which relate to data gathering conjunction with a law of nature or abstract idea such as Versata Dev. Group v. SAP Am., Inc., Intellectual Ventures I LLC v. Symantec Corp. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Step 2A – Prong 2: No.
Step 2B: As discussed with respect to step 2A Prong Two, the additional element in the
claims amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an
exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. The claims are ineligible. Step 2B: No.
Therefore, claims 1, 8, and 15 are ineligible under 35 U.S.C 101.
Claims 2-7, 9-14, and 16-20 recite limitations of determining foci points of an ellipse …, identifying of the object …, fitting a curvature of an ellipse …, and therefore these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea, furthermore, the additional elements in the claims 2-7, 9-14, and 16-20 are amount to no more than mere instructions to apply the exception using a generic computer component as discussed in step 2b in claim 1 above. Therefore, claims 2-7, 9-14, and 16-20 do not render them subject matter eligible under 35 U.S.C. 101 for similar reason as discussed in claim 1, 8, and 15.
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 1-5, 8-12 and 14-20 are rejected under 35 U.S.C. 102(a)(1) being anticipated by Cao (US 20250264593).
Regarding claim 1, Cao discloses a method comprising: obtaining a plurality of detection arcs corresponding to detection of an object using a plurality of ultra sonic sensors (obtaining sensor data using ultrasonic sensors (see include but are not limited to Fig. 2, paragraphs 0002, 0005-0006); and identifying the object based at least on an ellipse model applied to the plurality of detection arcs (Identifying the object based on the detections of plurality of sensors – see include but are not limited to Fig. 1 paragraphs 0007-0008).
Regarding claim 2, Cao discloses the method of claim 1, wherein application of the ellipse model to the plurality of detection arcs includes determining foci points of an ellipse based at least on the plurality of detection arcs (the sensor include focus points based on the detected object – see include but are not limited to Fig. 4B paragraph 0064).
Regarding claim 3, Cao discloses the method of claim 2, wherein the object is identified as corresponding to a particular point in space in response to a distance between the foci points approaching zero ( object is identified as the distance from the focus point to the object decrease – see include but are not limited to paragraph 0065-0069, 0116-0118).
Regarding claim 4, Cao discloses the method of claim 2, wherein the object is identified as corresponding to a planar surface in response to a distance between the foci points approaching infinity (the Time of Flight (TOF) value increase as the distance to object decrease – see include but are not limited to paragraphs 0007, 0116-0117).
Regarding claim 5, Cao discloses the method of claim 1, wherein the identifying of the object includes determining one or more of a shape of at least a portion of the object or a location of at least a portion of the object (identifying the shape of the object – see include but are not limited to paragraphs 0063-0064).
Regarding claim 8, Cao disclose a system comprising: one or more processors comprising processing circuitry to perform operations comprising identifying an object based at least on application of an ellipse model to a plurality of detections of an object using a plurality of sensors (obtaining sensor data using ultrasonic sensors. Identifying the object based on the detections of plurality of sensors – see include but are not limited to Fig. 1-2 paragraphs 0002, 0005-0008).
Regarding claim 9, Cao disclose the system of claim 8, wherein the ellipse model is applied to a plurality of detection arcs corresponding to the plurality of detections (the sensor include focus points based on the detected object – see include but are not limited to Fig. 4B paragraph 0064).
Regarding claim 10, Cao disclose the system of claim 8, wherein application of the ellipse model to the plurality of detection arcs includes determining foci points of an ellipse based at least on the plurality of detection arcs (the Time of Flight (TOF) value increase as the distance to object decrease – see include but are not limited to paragraphs 0007, 0116-0117).
Regarding claim 11, Cao disclose the system of claim 10, wherein: the object is identified as corresponding to a particular point in space in response to a distance between the foci points being less than a first threshold; the object is identified as corresponding to a planar surface in response to the distance between the foci points being greater than a second threshold; or the object is identified as corresponding to a curved surface in response to the distance between the foci points being between the first threshold and the second threshold (identifying the object based on the distance of the focus points – see include but are not limited to paragraphs 0065-0071).
Regarding claim 12, Cao disclose the system of claim 8, wherein the identifying of the object includes determining one or more of a shape of the object or a location of the object (identifying the shape of the object – see include but are not limited to paragraphs 0063-0064).
Regarding claim 14, Cao disclose the system of claim 8, wherein the system corresponds to one or more of: a control system for an autonomous or semi-autonomous machine a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; 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 for presenting at least one of augmented reality content, virtual reality content, or mixed reality content; a system for hosting one or more real-time streaming applications; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system for performing one or more generative AI operations; a system implementing one or more large language models (LLMs); a system implementing one or more vision language models (VLMs); 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 (control system for autonomous semi-autonomous vehicle; the detection system for autonomous semi-autonomous vehicle; system include sensor; system implemented using a machine – see include but are not limited to Fig. 16 paragraphs 0002, 0051, 0065, 0219, 0222-0223).
Regarding claim 15, Cao disclose a processing system comprising: one or more processors to perform operations comprising: applying an ellipse model to detection data corresponding to a plurality of detections of an object using a plurality of sensors (obtaining sensor data using ultrasonic sensors (see include but are not limited to Fig. 2, paragraphs 0002, 0005-0006); and identifying the object based at least on one or more ellipsoidal parameters determined based at least on application of the ellipse model to the detection data (obtaining sensor data using ultrasonic sensors. Identifying the object based on the detections of plurality of sensors – see include but are not limited to Fig. 1-2 paragraphs 0002, 0005-0008).
Regarding claim 16, Cao disclose the processing system of claim 15, wherein the one or more ellipsoidal parameters include one or more of: one or more ellipse focal points (the sensor include focus points based on the detected object – see include but are not limited to Fig. 4B paragraph 0064); an ellipse major axis; an ellipse minor axis; or a curvature of ellipse(the detection include x and y axis – see include but are not limited to paragraph 0178);.
Regarding claim 17, Cao disclose the processing system of claim 15, wherein: the object is identified as corresponding to a particular point in space based at least on the one or more ellipsoidal parameters (the sensor include focus points based on the detected object – see include but are not limited to Fig. 4B paragraph 0064); the object is identified as corresponding to a planar surface based at least on the one or more ellipsoidal parameters (identifying object as the distance from the sensor to the TOF decrease – see include but are not limited to paragraphs 0063-0064, 0141, 0178); or the object is identified as corresponding to a curved surface based at least on the one or more ellipsoidal parameters (object is identified based on the reflection surface of the object – see include but are not limited to Fig. 7A paragraph 0108).
Regarding claim 18, Cao disclose the processing system of claim 15, wherein the identifying of the object includes determining one or more of a shape of the object or a location of the object (identifying the shape of the object – see include but are not limited to paragraphs 0063-0064).
Regarding claim 19, Cao disclose the processing system of claim 15, wherein the applying of the ellipse model to the detection data includes: determining a plurality of detection arcs based at least on the detection data (determined plurality of ultrasonic waves based on detection data – see include but are not limited to Fig.2 paragraphs 0053, 0065); and applying the ellipse model to one or more parameters corresponding to the plurality of detection arcs (applying reflection point model to the identified object – see include but are not limited to Fig.4B paragraph 0076).
Regarding claim 20, Cao disclose the processing system of claim 15, wherein the detection data indicates respective distances from the plurality of sensors to the object and the applying of the ellipse model to the detection data is based at least on the respective distances (the reflecting point model is apply based on the distance between the object and the sensors – see includes but are not limited to Fig.5B, paragraphs 0065, 0076-0079).
Claim Rejections - 35 USC § 103
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 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.
Claims 6-7 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Cao et al. (US 20250264593) in view of Sajjan et al (US 20230213945).
Regarding claim 6, Cao discloses the method of claim 1, wherein application of the ellipse model to the plurality of detection arcs includes (applying reflection point model to the identified object – see include but are not limited to Fig.4B paragraph 0076)
However, Cao does not explicitly disclose fitting a curvature of an ellipse to the plurality of detection arcs.
Sajjan discloses fitting a curvature of an ellipse to the plurality of detection arcs (fitting curvature of an ellipse to detection arc – see include but are not limited to Fig.9B).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify Cao with the teaching of fitting a curvature of an ellipse to the plurality of detection arcs as taught by Sajjan in order to yield predicable result of allow camera and sensor to have wider view [0108] .
Regarding claim 7, Cao in view of Sajjan disclose the method of claim 6, as discussed supra with respect to same.
Saijja teaches, wherein a shape of the object is determined based at least on the curvature of the ellipse (shape of object is determined based on the curvature of the ellipse see includes but are not limited to Fig. 9B paragraph 0002-0003, 0032).
Regarding claim 13, Cao discloses the system of claim 1, wherein application of the ellipse model to the plurality of detection arcs includes (applying reflection point model to the identified object – see include but are not limited to Fig.4B paragraph 0076)
However, Cao does not explicitly disclose fitting a curvature of an ellipse to the plurality of detection arcs.
Sajjan discloses fitting a curvature of an ellipse to the plurality of detection arcs (fitting curvature of an ellipse to detection arc – see include but are not limited to Fig.9B).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify Cao with the teaching of fitting a curvature of an ellipse to the plurality of detection arcs as taught by Sajjan in order to yield predicable result of allow camera and sensor to have wider view [0108].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's
disclosure:
Sithiravel et al. (US 20230417857) discloses using plurality of ultrasonic sensors to detect objects on the road.
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/A.K.T./Examiner, Art Unit 3665
/CHRISTIAN CHACE/Supervisory Patent Examiner, Art Unit 3665