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
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)(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) 11-13 and 17 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Nakamura (US 2021/0141090).
With regard to claim 11, Nakamura discloses a method for detecting dirt on a viewing window of a LIDAR, comprising (see Fig. 4A, distance data reliability determination for dirt detection, and paragraphs [0067-0068] ):
transmitting, by a transmitter of the lidar, a laser beam into a detection region (emission control signal in first or second exposure period, Fig. 3);
detecting, using a receiver of the lidar, light present in the detection region without transmitting the laser beam (third exposure period (b3);
generating an intensity image as a greyscale image of intensities of laser reflections from light reflected and detected as a result of the transmission of the laser beam (light intensity for each pixel is combined to form an intensity image, para. [0060] & [0085]);
generating a background light image as a greyscale image of background light from the light detected without transmitting the laser beam (Fig. 3, third exposure period without emission control signal for transmitting laser beam) ;
analyzing the intensity image and the background light image for common features; and determining that there is dirt on the viewing window when a number of common features between the intensity image and the background light image is below a predetermined number (signal level difference arising under the presence of dirt (comparison of Fig. 6B(b) shows common features “first distance” and “second distance” based on pixel threshold, and determination that common features are absent (below threshold) when dirt is present, paras. [0086-0087]. Note: Examiner has interpreted Fig. 6B according to the text in the Specification, rather than the legend text for the Figure).
With regard to claim 12, the laser beam is transmitted in pulses (Fig. 3, [0012]).
With regard to claim 13, light in the detection region is detected prior to transmission of laser pulses of the next set of exposure period (e. g. Fig. 3 third exposure period of first set is before first exposure period of next set, [0057]).
With regard to claim 17, Nakamura discloses a device for detecting dirt on a viewing window of a LIDAR, comprising
The LIDAR (Fig. 1, including emitter (transmitter) and light receiver with solid state image sensor)
a processor (Fig. 2, data processor 103) coupled to the lidar, wherein the processor is configured to instruct a transmitter of the lidar to transmit a laser beam into a detection region (emission control signal in first or second exposure period, Fig. 3);
instruct a receiver of the lidar to detect light present in the detection region without transmitting the laser beam (third exposure period (b3));
generate an intensity image as a greyscale image of intensities of laser reflections from light reflected and detected as a result of the transmission of the laser beam (light intensity for each pixel is combined to form an intensity image, para. [0060] & [0085]);
generate a background light image as a greyscale image of background light from the light detected without transmitting the laser beam (Fig. 3, third exposure period without emission control signal for transmitting laser beam); analyze the intensity image and the background light image for common features; and determine that there is dirt on the viewing window when a number of common features between the intensity image and the background light image is below a predetermined number (comparison of Fig. 6B(b) shows common features “first distance” and “second distance” based on pixel threshold, and determination that common features are absent (below threshold) when dirt is present, paras. [0086-0087]. Note: Examiner has interpreted Fig. 6B according to the text in the Specification, rather than the legend text for the Figure).
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) 14-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nakamura as applied to claim 11 above, and further in view of Tisdale et al. (US2019/0033459).
Nakamura does not disclose, but Tisdale teaches in the same field of endeavor, edge detection (para. [0070]) in order to compare a grayscale image from the LIDAR data to a reference image, which may be of a building or vehicle (para. [0050]). The edge positions and distances are identified as features based on the recognized edges of the reference image (LIDAR used to identify features, [0064]). It would have been obvious to one skilled in the art, e. g. an optical engineer, before the effective filing date of the application, to include the edge detection algorithm to identify edge distances or positions as taught by Tisdale et al. in the method of operating the LIDAR of Nakamura for the advantage of faster determination of obstacles and/or position and orientation of a vehicle on which the LIDAR is mounted (Tisdale paras. [0032], [0072] & [0075]).
Claims 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Nakamura (US 2021/0141090) and Tisdale et al. (US2019/0033459).
With regard to claim 18, Nakamura discloses Nakamura discloses a device for detecting dirt on a viewing window of a LIDAR, comprising
The LIDAR (Fig. 1, including emitter (transmitter) and light receiver with solid state image sensor)
a processor (Fig. 2, data processor 103) coupled to the lidar, wherein the processor is configured to instruct a transmitter of the lidar to transmit a laser beam into a detection region (emission control signal in first or second exposure period, Fig. 3);
instruct a receiver of the lidar to detect light present in the detection region without transmitting the laser beam (third exposure period (b3));
generate an intensity image as a greyscale image of intensities of laser reflections from light reflected and detected as a result of the transmission of the laser beam (light intensity for each pixel is combined to form an intensity image, para. [0060] & [0085]);
generate a background light image as a greyscale image of background light from the light detected without transmitting the laser beam (Fig. 3, third exposure period without emission control signal for transmitting laser beam); analyze the intensity image and the background light image for common features; and determine that there is dirt on the viewing window when a number of common features between the intensity image and the background light image is below a predetermined number (comparison of Fig. 6B(b) shows common features “first distance” and “second distance” based on pixel threshold, and determination that common features are absent (below threshold) when dirt is present, paras. [0086-0087]. Note: Examiner has interpreted Fig. 6B according to the text in the Specification, rather than the legend text for the Figure).
Nakamura does not disclose, but Tisdale et al. teach a motor vehicle comprising a LIDAR and associated processor coupled to the LIDAR (Fig. 1, para. [0041]). The integration of the LIDAR into the vehicle results in improved obstacle avoidance and navigation (para. [0038]). Therefore, it would have been obvious to one skilled in the art, e. g. an optical or automotive engineer, to configure the LIDAR system of Nakamura into the motor vehicle as taught by Tisdale, before the effective filing date of the application.
With regard to claim 19, Tisdale teaches that the vehicle may be autonomous (para. [0041]).
Information Disclosure Statement
The information disclosure statements filed on May 17, 2023, March 18, 2024, March 11, 2025, and Sept. 17, 2025 have been considered by the Examiner.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Astrom discloses LIDAR with contamination detection.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to ERIC L BOLDA whose telephone number is 571-272-8104. The examiner can normally be reached on M-F from 8:30am to 5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, YUQING XIAO can be reached on 571-270-3603. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ERIC L BOLDA/ Primary Examiner, Art Unit 3645