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 .
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.
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.
Claims 1, 2, 5, 6, 9, 10, 14, and 16-18 are rejected under 35 U.S.C. 102(a)(1) and/or 102(a)(2) as being anticipated by Ebrahimi Afrouzi et al. (US 11,449,061).
As to claim 1, Ebrahimi Afrouzi discloses an apparatus (FIGS. 2A-2B; col. 36, lines 47-55) comprising:
a light detection and ranging (LiDAR) system comprising an emitter configured to perform an initial scan of light beams across a field of view (FoV) and a detector configured to generate range information associated with a potential target down range from the LiDAR system responsive to the initial scan (col. 34, lines 50-66; col. 36, lines 47-65);
an external sensor configured to sense external information associated with the potential target within the FoV (col. 34, lines 50-66; col. 36, lines 47-65); and
a criteria based learning circuit configured to identify a false positive condition associated with the range information from the potential target by combining the external information from the external sensor with detection information obtained from the detector during a subsequent scan by the emitter (col. 34, lines 50-66; col. 36, lines 47-65; col. 59, lines 30-37).
The same reasoning applies, mutatis mutandis, to the subject-matter of the corresponding independent claim 15, which therefore is also considered as being anticipated by Ebrahimi Afrouzi.
As to claim 2, Ebrahimi Afrouzi further discloses that the external sensor comprises a camera which operates to collect ambient light from the FoV from a vicinity adjacent the potential target (col. 13, lines 31-35).
As to claim 5, Ebrahimi Afrouzi further discloses that the LiDAR system actively emits and detects light beams over a first range of wavelengths and the external sensor passively receives light beams over a different, second range of wavelengths (col. 13, lines 31-49, Ambient solar has wavelengths in the solar spectrum, which would differ from the emitted and detected light wavelengths).
As to claim 6, Ebrahimi Afrouzi further discloses that the criteria based learning system uses an artificial neural network to determine the presence or absence of a physical element corresponding to the detected potential target (col. 150, lines 25-31; col. 194, lines 34-46; col. 208, lines 17-25; col. 256, lines 18-23).
As to claim 9, Ebrahimi Afrouzi further discloses that the detected potential target has a first overall boundary area within the FoV from the detector, and the criteria based learning circuit directs the external sensor to scan an area within the FoV that includes the first overall boundary area as well as a second surrounding area adjacent the first overall boundary area (col. 36, line 47 to col. 37, line 65).
As to claim 10, Ebrahimi Afrouzi further discloses that the subsequent scan is provided with a first resolution and frame rate, and the external information from the external sensor is provided with a higher, second resolution and a second, lower frame rate (col. 206, lines 25-28).
As to claim 14, Ebrahimi Afrouzi further discloses that the criteria based learning circuit is realized as at least one programmable processor which executes corresponding program instructions stored in an associated memory (col. 12, lines 21-26).
As to claim 16, Ebrahimi Afrouzi further discloses that the external sensor is characterized as a camera which passively collects light from the FoV to generate the external information (col. 13, lines 31-35).
As to claim 17, Ebrahimi Afrouzi further discloses activating the external sensor to scan a vicinity of the potential target responsive to the range information associated with the potential target meeting or exceeding a predetermined threshold (col. 130, line 53 to col. 131, line 14).
As to claim 18, Ebrahimi Afrouzi further discloses using an artificial neural network circuit to differentiate between the true detection condition and the false positive condition regarding the potential target (col. 150, lines 25-31).
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 7 is rejected under 35 U.S.C. 103 as being unpatentable over Ebrahimi Afrouzi in view of Zagorski (US 2010/0094520).
As to claim 7, Ebrahimi Afrouzi teaches the apparatus of claim 1, as discussed above. However, Ebrahimi Afrouzi does not teach that the criteria based learning circuit is further configured to determine that a physical element is present downrange from the LiDAR system corresponding to the potential target, but further determines that at least one aspect of the corresponding range information detected from the detector is erroneous using the external sensor. Zagorski teaches that camera data can be used to validate the lidar data (paragraph [0016], “Obstacle detection related information or data from the first sensor 13 [Zagorski’s camera] can be used to validate the corresponding data or information from the second sensor 17 [Zagorski’s lidar] …”), and therefore suggests that the criteria based learning circuit is further configured to determine that a physical element is present downrange from the LiDAR system corresponding to the potential target, but further determines that at least one aspect of the corresponding range information detected from the detector is erroneous using the external sensor, since a validation effort implies that the second sensor data could be erroneous. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the apparatus of claim 1 as taught by Ebrahimi Afrouzi, in combination with that the criteria based learning circuit is further configured to determine that a physical element is present downrange from the LiDAR system corresponding to the potential target, but further determines that at least one aspect of the corresponding range information detected from the detector is erroneous using the external sensor as suggested by Zagorski, since such combination enables correct possible erroneous data from one sensor when multiple sensors are in use.
Claims 8 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ebrahimi Afrouzi in view of Izzat et al. (US 2017/0307743).
As to claim 8, Ebrahimi Afrouzi teaches the apparatus of claim 1 as discussed above. However, Ebrahimi Afrouzi does not teach that the criteria based learning circuit increases a density of beam points in a vicinity of the potential target during the subsequent scan. Izzat teaches choice of beam FOV and pixel size for adaptation of resolution (paragraphs [0016], [0019], [0029]), and therefore suggests that the criteria based learning circuit increases a density of beam points in a vicinity of the potential target during the subsequent scan. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the apparatus of claim 1 as taught by Ebrahimi Afrouzi, in combination with the criteria based learning circuit increasing a density of beam points in a vicinity of the potential target during the subsequent scan as suggested by Izzat, since such combination improves vehicle safety during driving.
As to claim 19, Ebrahimi Afrouzi teaches the method of claim 15 as discussed above. However, Ebrahimi Afrouzi does not teach that a first scan profile having a first beam point density is used during the initial scan and a different, second scan profile having a higher second beam point density is used during the subsequent scan. Izzat teaches choice of beam FOV and pixel size for adaptation of resolution (paragraphs [0016], [0019], [0029]), and therefore suggests that a first scan profile having a first beam point density is used during the initial scan and a different, second scan profile having a higher second beam point density is used during the subsequent scan. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the method of claim 15 as taught by Ebrahimi Afrouzi, in combination with a first scan profile having a first beam point density being used during the initial scan and a different, second scan profile having a higher second beam point density being used during the subsequent scan as suggested by Izzat, since such combination improves vehicle safety during driving.
Claims 11 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Ebrahimi Afrouzi.
As to claim 11, Ebrahimi Afrouzi teaches the apparatus of claim 1 as discussed above. However, Ebrahimi Afrouzi does not teach that the criteria based learning circuit declares a true condition exists based on detection, by the external sensor, of a physical element corresponding to the target detected by the LiDAR system. Nonetheless, to one of ordinary skill in the art, such additional limitation would have been an obvious feature to add to the apparatus of claim 1, since it merely enables providing notice of such detection.
As to claim 12, Ebrahimi Afrouzi teaches the apparatus of claim 1 as discussed above. However, Ebrahimi Afrouzi does not teach that the criteria based learning circuit declares a false positive condition exists based on a lack of detection, by the external sensor, of a physical element corresponding to the target detected by the LiDAR system. Nonetheless, to one of ordinary skill in the art, such additional limitation would have been an obvious feature to add to the apparatus of claim 1, since it merely enables providing notice of such lack of detection.
Allowable Subject Matter
Claims 3, 4, 13, 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
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
The references made herein are done so for the convenience of the applicant. They are in no way intended to be limiting. The prior art should be considered in its entirety.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL L MURPHY whose telephone number is (571)270-3194. The examiner can normally be reached M-F 9-5.
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.
/DANIEL L MURPHY/Primary Examiner, Art Unit 3645