DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status
2. This communication is in response to the Preliminary Amendment filed on 07.01.2024. Applicant amended paragraph [0010] of the Specification, and no amendments to the claims. Therefore, claims 1-20 will be subject to further examination and evaluation in due course, and will be presented for examination, as detailed below.
Oath/Declaration
3. The Applicant's oath/declaration has been reviewed by the Examiner and is found to conform to the requirements prescribed in 37 C.F.R. 1.63.
Information Disclosure Statement
4. As required by M.P.E.P. 609(C), the Applicant's submission of the Information Disclosure Statement (IDS) dated 06.14.2024 is acknowledged by the Examiner. The cited references have been considered in the examination of the claims. As required by M.P.E.P 609 C (2), a copy of the PTOL-1449 initialed, signed and dated by the Examiner is attached to the instant Office action.
Priority / Filing Date
5. Applicant's claim for priority of the PRO 63/508,781 Application filed on 06.16.2023 is acknowledged. The Examiner takes the PRO date of 06.16.2023 into consideration.
Claim Rejections - 35 USC § 103
6. 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.
7. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
8. Claims 1-7 are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al., Pub. No.: US 11,385,335 in view of Ferreira et al., Pub. No.: US 2020/0284883.
As per claim 1, Wu discloses a system, comprising: at least one memory storing instructions [see at least ¶0015 (e.g., a LiDAR system for a vehicle can include one or more processors; and one or more non-transitory computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations), as illustrated in FIG. 9 (e.g., block 906 storage system), and shown below]:
FIG. 9 shows a system for operating a LiDAR-based detection system.
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and at least one processor in communication with the at least one memory [as illustrated in FIG. 2 (e.g., block 220), and shown below], wherein the at least one processor is configured to execute the stored instructions to: control a light detection and ranging (LiDAR) sensor to emit a pulse into an environment of the LiDAR sensor [see at least ¶0032 (e.g., (see, e.g., FIG. 2) may use a pulsed light source (e.g., focused light, lasers, etc.) and detection system to detect external objects and environmental features (e.g., vehicles, structures, etc.), determine the vehicle's position, speed, and direction relative to the detected external objects, and in some cases may be used to determine a probability of collision, avoidance strategies, or otherwise facilitate certain remedial actions), and shown below]:
FIG. 2 shows aspects of a LiDAR-based detection system.
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determine a noise threshold corresponding to the ambient light [see at least the abstract (e.g., method for operating a LiDAR system in an automobile that can include receiving noise data corresponding to an ambient noise level, receiving false positive data corresponding to a rate of false positive object detection occurrences; determining an object detection range spanning a distance defined by a minimum range of object detection and a maximum range of object detection for the LiDAR system; generating an object detection threshold value for detecting objects based on the noise data and the rate of false positive data; applying the object detection threshold value to each of a plurality of range values within the object detection range; and applying a gain sensitivity profile to the object detection threshold value at each of a plurality of range values)] ; determine a peak of a plurality of peaks that has a maximum intensity [see at least ¶0050 (e.g., the object detection threshold may be applied to the maximum range (furthest detectable distance) with the object detection threshold for distances ranging from the minimum detection range up to the maximum range being modified by a gain sensitivity model (e.g., Lambertian model), as described below with respect to FIG. 4), and shown below]; and add the peak to a point cloud [see at least ¶0037 (e.g., forming a “point cloud.” The point cloud data can be used to estimate, for example, a distance, dimension, and location of the object relative to the LiDAR system, often with a very high fidelity (e.g., within 2 cm). In some cases, a third dimension (e.g., height) may be performed in a number of different manners)]:
FIG. 4 shows a graph plotting a gain factor versus a range in a LiDAR-based detection system.
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Wu discloses all elements per claimed invention as explained above. Wu, further discloses waveform [see at least ¶0042 (e.g., generate a continuous or pulsed laser beam at any suitable electromagnetic wavelengths spanning the visible light spectrum and non-visible light spectrum (e.g., ultraviolet and infra-red). In some embodiments, lasers are commonly in the range of 600-1200 nm, although other wavelengths are possible)]; return signal [see at least ¶0043 and ¶0045]; noise data [see at least ¶0050 (e.g., detected by one or more microphones) corresponding to an ambient noise level, and false positive data (typically a constant value) corresponding to a rate of false positive object detection occurrences for the LiDAR system]; and a LiDAR system using parallel detectors with different operating thresholds and a corresponding arbitration logic to improve accuracy can be used (see, e.g., FIGS. 7-8), and as shown below.
FIG. 7 shows a LiDAR system receiver module with parallel detectors.
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FIG. 8 shows a simplified flow chart showing a method for detecting one or more objects in a multi-receiver LiDAR-based system using an arbitration logic.
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Wu does not explicitly recite “temporal histogram”. However, Ferreira discloses generate temporal histograms [see at least Ferreira ¶0489 (e.g., FIG. 14 shows a block diagram of a LIDAR setup for time gated measurement on base of statistical photon count evaluation at different time window positions during the transient time of the laser pulse. The position of the gated window 1404 which correlates to the distance do of the observed (in other words targeted) object 100 may be set and scanned either by the host controller 62 itself or by the trigger-based pre-evaluation of the incoming detector signal (event-based measuring). The predefined width of the gate window 1404 determines the temporal resolution and therefore the resolution of the objects' 100 depth measurement. For data analysis and post processing, the resulting measurements in the various time windows 1404 can be ordered in a histogram which then represents the backscattered intensity in correlation with the depth, in other words, as a function of depth), ¶2931 (e.g., a histogram (e.g., a distribution, for example a frequency distribution) of the determined running times. Illustratively, the one or more processors may be configured to group the determined running times (e.g., to create a histogram based on the grouping of the determined running times). The one or more processors may be configured to classify the one or more sensor pixel signals based on the determined histogram), and as show below]:
FIG. 14 shows a block diagram of a LIDAR setup for time gated measurement based on statistical photon count evaluation at different time window positions during the transient time of the laser pulse in accordance with various embodiments.
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Therefore, it would have been obvious to a person having ordinary skill in the art at the time the invention was made to incorporate the teaching of Ferreira in order to provide light detection and ranging (LIDAR) systems and methods that use light detection and ranging technology [Ferreira: ¶0002].
As per claim 2, Wu discloses wherein to denoise the temporal waveform, the at least one processor is further configured to denoise the temporal waveform generated based on the temporal histograms by convolving the waveform with the pulse emitted by the LiDAR sensor [see at least the rejection of claim 1 above. Similar rationale is noticed for the combination of Wu and Ferreira, as noted in claim 1 above. In light of the preceding examination, claim 2 is hereby rejected on grounds substantially similar to those articulated in the rejection of claim 1. As detailed in the prior rejection, the rationale and basis for rejecting claim 1 are applicable to claim 2. For a comprehensive understanding of the rejection grounds, reference is made to the detailed explanation provided in the rejection of claim 1, which is incorporated herein by reference].
A per claim 3, Wu discloses wherein to estimate the ambient light, the at least one processor is further configured to remove the temporal waveform’s median from noisy and saturated waveforms [see at least the rejection of claim 1 above. Similar rationale is noticed for the combination of Wu and Ferreira, as noted in claim 1 above. In light of the preceding examination, claim 3 is hereby rejected on grounds substantially similar to those articulated in the rejection of claim 1. As detailed in the prior rejection, the rationale and basis for rejecting claim 1 are applicable to claim 3. For a comprehensive understanding of the rejection grounds, reference is made to the detailed explanation provided in the rejection of claim 1, which is incorporated herein by reference].
As per claim 4, Wu discloses wherein the at least one processor is further configured to recover true intensity of the peak by compensating the maximum intensity of the peak using a half pulse width and power level of the pulse as scaling factors [see at least the rejection of claim 1 above. Similar rationale is noticed for the combination of Wu and Ferreira, as noted in claim 1 above. In light of the preceding examination, claim 4 is hereby rejected on grounds substantially similar to those articulated in the rejection of claim 1. As detailed in the prior rejection, the rationale and basis for rejecting claim 1 are applicable to claim 4. For a comprehensive understanding of the rejection grounds, reference is made to the detailed explanation provided in the rejection of claim 1, which is incorporated herein by reference].
As per claim 5, Wu discloses wherein the at least one processor is further configured to determine an edge threshold as a continuous parameter having a value between 0 and 2, wherein the continuous parameter is the determined noise threshold [see at least ¶0059 (e.g., FIG. 5 is a simplified flow chart showing a method 500 for modifying an object detection threshold value across a range using a gain sensitivity profile, according to certain embodiments), and as shown below]:
FIG. 5 is a simplified flow chart showing a method for modifying an object detection threshold value across a range using a gain sensitivity profile.
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As per claim 6, Wu discloses wherein a power level of the pulse emitted by the LiDAR sensor is selected from a plurality of power levels [see at least ¶0043 (e.g., Power block 215), and as illustrated in FIG. 2 above].
As per claim 7, Wu discloses wherein a pulse duration of the emitted pulse ranges from 3 nano seconds (ns) to 15 ns [see at least ¶0068 (e.g., light signal generator 230 may generate a laser pulse (e.g., 5 ns duration))].
9. Claims 8-14, which are parallel to claims 1-7 in terms of scope,
limitations, and share similar characteristics, as discussed and examined
above. Consequently, they are rejected based on the same logical and
underlying reasoning, and justification that apply to claims 1-7. The
similarity between these claims necessitates the same grounds for rejection, as explained in detail above [note the discussion of claims 1-7].
10. Claims 15-20, which are parallel to claims 1-7 in terms of scope,
limitations, and share similar characteristics, as discussed and examined
above. Consequently, they are rejected based on the same logical and
underlying reasoning, and justification that apply to claims 1-7. The
similarity between these claims necessitates the same grounds for rejection, as explained in detail above [note the discussion of claims 1-7].
Conclusion
11. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2018/0128920, Keilaf: discloses systems and methods that use LIDAR technology to detect objects in the surrounding environment.
US 10,983,200, Shen: discloses polarization management in a light detection and ranging (LiDAR) system.
WO 2022076229, Hostetler: discloses Light detection and ranging (LiDAR) systems.
US 2020/0341144, Pacala: discloses Light Detection and Ranging (LIDAR) systems for object detection and ranging, e.g., for vehicles such as cars, trucks, boats, etc.
12. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Garcia Ade whose telephone number is (571)272-5586. The examiner can normally be reached on Monday - Friday.
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, Florian Zeender can be reached on 517-272-6790. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
13. 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.
/Garcia Ade/Primary Examiner, Art Unit 3627
GARCIA ADE
Primary Examiner
Art Unit 3687
/GA/Primary Examiner, Art Unit 3627
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