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 .
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.
Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Each of claims 1-12 falls within one of the four statutory categories. See MPEP § 2106.03. For example, each of claims 1-7 and 15-20 falls within category of machine, i.e., a “concrete thing, consisting of parts, or of certain devices and combination of devices.” Digitech, 758 F.3d at 1348–49, 111 USPQ2d at 1719 (quoting Burr v. Duryee, 68 U.S. 531, 570, 17 L. Ed. 650, 657 (1863)) and For example, each of claims 8-14 a falls within category of process.
Regarding claims 1-7
Step 2A – Prong 1
Exemplary claim 1 is directed to an abstract idea of determining a new centroid corresponding to the computed transient.
The abstract idea is set forth or described by the following italicized limitations:
1. A system, comprising:
at least one memory storing instructions; and
at least one processor in communication with the at least one memory, wherein the at least one processor is configured to execute the stored instructions to:
initiate optimization of a pulse emitted by a light detection and ranging (LiDAR) sensor into an environment of the LiDAR sensor using a respective channel of a plurality of channels of the LiDAR sensor;
initiate optimization of a pipeline processing a signal corresponding to the emitted pulse received at a detector of the LiDAR sensor;
construct a max-rank loss scalarization for the signal using the optimized pipeline;
compute transients using centroid weights based upon the max-rank loss scalarization; and
replace a centroid based upon a covariance matrix adaptation-evolution strategy (CMA-ES) upon determining a new centroid corresponding to the computed transients..
The bold limitations above represent a mathematical concepts (i.e., a process that can be performed by mathematical relationships or rules or idea). Therefore, the bold limitations fall within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance.
For example, the limitations “initiate optimization of a pipeline processing a signal corresponding to the emitted pulse received at a detector of the LiDAR sensor; construct a max-rank loss scalarization for the signal using the optimized pipeline; compute transients using centroid weights based upon the max-rank loss scalarization; and replace a centroid based upon a covariance matrix adaptation-evolution strategy (CMA-ES) upon determining a new centroid corresponding to the computed transients.” a mathematical concepts (i.e., a process that can be performed by mathematical relationships or rules or idea.
Limitations are considered together as a single abstract idea for further analysis. (discussing Bilski v. Kappos, 561 U.S. 593 (2010)).
Step 2A – Prong 2
Claims 1 does not include additional elements (when considered individually, as an ordered combination, and/or within the claim as a whole) that are sufficient to integrate the abstract idea into a practical application.
For example,1st additional first element is “initiate optimization of a pulse emitted by a light detection and ranging (LiDAR) sensor into an environment of the LiDAR sensor using a respective channel of a plurality of channels of the LiDAR sensor” to be performed, at least in-part, these additional elements appear to only add insignificant extra-solution activity (e.g., data gathering and or pre solution activity and /or field of use) and only generally link the abstract idea to a particular field. Therefore, this element individually or as a whole does not provide a practical application. See MPEP 2106.05(f).
The 2nd additional element is “a pulse emitted by a light detection and ranging (LiDAR) sensor into an environment of the LiDAR sensor using a respective channel of a plurality of channels of the LiDAR sensor”. This element amounts to mere use of a generic LiDar system, which is well understood routine and conventional (see background of current discloser and IDS and PTO 892) and this element individually does not provide a practical application. In view of the above, the “additional element” individually or combine does not provide a practical application of the abstract idea. see MPEP 2106.05(d).
The 3rd additional element is “A system, comprising: at least one memory storing instructions; and at least one processor in communication with the at least one memory, wherein the at least one processor is configured to execute the stored instructions to:”. This element amounts to mere use of a generic computer component, which is well understood routine and conventional (see background of current discloser and IDS and PTO 892) and this element individually does not provide a practical application. In view of the above, the “additional element” individually or combine does not provide a practical application of the abstract idea. see MPEP 2106.05(d).
In view of the above, the “additional elements” individually do not provide a practical application of the abstract idea. Furthermore, the “additional elements” in combination amount to a plurality of generic component with software, where such computers and software amount to mere instructions to implement the abstract idea on a computer(s) and/or mere use of a generic computer component(s) as a tool to perform the abstract idea. Therefore, these elements in combination do not provide a practical application. The combination of additional elements does no more than generally link the use of the abstract idea to a particular technological environment, and for this additional reason, the combination of additional elements does not provide a practical application of the abstract idea. Noting MPEP 2106.04(d)(I): “It is notable that mere physicality or tangibility of an additional element or elements is not a relevant consideration in Step 2A Prong Two. As the Supreme Court explained in Alice Corp., mere physical or tangible implementation of an exception does not guarantee eligibility. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1983-84 (2014) ("The fact that a computer ‘necessarily exist[s] in the physical, rather than purely conceptual, realm,’ is beside the point")”.
Step 2B
Claims1 does not include additional elements, when considered individually and as an ordered combination, that are sufficient to amount to significantly more than the abstract idea. For example, the limitation of Claim 1 contains additional elements that are, i.e. “Lidar, processor, memory, vehicle (as cited in claim 15) ”, generic device and component, which are well understood, routine and convention (see background of current discloser and IDS and PTO 892) and MPEP 2106.05(d))The reasons for reaching this conclusion are substantially the same as the reasons given above in § Step 2A – Prong 2. For brevity only, those reasons are not repeated in this section. See MPEP §§ 2106.05(g) and MPEP §§2106.05(II).
.
Dependent Claims 2-7
Dependent claims 2-7 fail to cure this deficiency of independent claim 1 (set forth above) and are rejected accordingly. Particularly, claims 2-7 recite limitations that represent (in addition to the limitations already noted above) either the abstract idea of mathematical concepts (bold) or an additional element that is merely extra-solution activity(data gathering)(italicized), mere use of instructions and/or generic components and/computer component(s) as a tool to implement the abstract idea, and/or merely limits the abstract idea to a particular technological environment(under line).
For examples:
2. to modulate the pipeline using a set of hyperparameters.
3. the set of hyperparameters includes a rising edge threshold, a laser power of the emitted pulse, and a laser pulse width of the pulse.
4. the modulated pipeline maps a set of truncated waveforms to a point cloud including compressed information to downstream detectors.
5. the max-rank loss scalarization is dynamic.
6. the max-rank loss scalarization is a stable max-rank loss scalarization based on keeping a weight associated with each loss vector fixed.
7. the max-rank loss scalarization is a stable max-rank loss scalarization based on stabilizing the weighted max-rank loss with respect to loss value tie breaking from noise and quantization..
Regarding Claims 8-20
Claims 8-20 contains language similar to claim 1-7 as discussed in the preceding paragraphs, and for reasons similar to those discussed above, claims 8-20 are also rejected under 35 U.S.C. § 101(abstract idea).
Allowable Subject Matter
There is no prior art rejection over claims1-20, however there is 101 rejection. The closets prior art, Kim et al. (US 2025/0086759) discloses the LiDAR 120 may obtain datasets including a plurality of points in a three-dimensional space (e.g., represented by an x-axis, a y-axis, and a z-axis), based on a pulse laser signal reflected from the one or more objects. For example, the LiDAR 120 may obtain the datasets including the plurality of points in the space (e.g., represented by the x-axis, the y-axis, and the z-axis), based on receiving a pulse laser signal at a specified period.
Parikh et al. (US 2024/0428596) disclose the 3D part of the cost function may use one or more features. For example, a position (or range) difference may be used. To account for varying track and measurement uncertainties, scaling may be used. One option for scaling may be to use the uncertainty of the prediction and the measurement noise—e.g., by using a Mahalanobis distance. Another option for scaling is to use the method described herein with respect to gating. The azimuth difference (e.g., in rig coordinates) is another feature that may be used for the 3D part of the cost function. Scaling may be used for the Azimuth difference as well.
Westman et al. (US 2024/0242369) disclose As will be described in greater detail, AV 102a may be configured with a lidar system, e.g., lidar system 264 of FIG. 2. The lidar system may be configured to transmit a light pulse 104 to detect objects located within a distance or range of distances of AV 102a. Light pulse 104 may be incident on one or more objects (e.g., AV 102b) and be reflected back to the lidar system. Reflected light pulse 106 incident on the lidar system may be processed to determine a distance of that object to AV 102a. The reflected light pulse may be detected using, in some embodiments, a photodetector or array of photodetectors positioned and configured to receive the light reflected back into the lidar system. Where k is the number of point neighbors considered in the neighborhood of p.sub.i, p is the 3D centroid of the nearest neighbors, λ.sub.j is the j-th eigenvalue of the covariance matrix, and v.sub.j is the j-th eigenvector of the covariance matrix.
Pavone et al. (US 2024/0199068) disclose SoC(s) 604 may be used to process data from cameras (e.g., connected over Gigabit Multimedia Serial Link and Ethernet channels), sensors (e.g., LIDAR sensor(s) 664, RADAR sensor(s) 660, etc. that may be connected over Ethernet channels), data from bus 602 (e.g., speed of vehicle 600, steering wheel position, etc.), data from GNSS sensor(s) 658 (e.g., connected over a Ethernet bus or a CAN bus), etc. In at least one embodiment, one or more SoC of SoC(s) 604 may further include dedicated high-performance mass storage controllers that may include their own DMA engines, and that may be used to free CPU(s) 606 from routine data management tasks. In at least one embodiment, vehicle 600 may include LIDAR sensor(s) 664. In at least one embodiment, LIDAR sensor(s) 664 may be used for object and pedestrian detection, emergency braking, collision avoidance, and/or other functions. In at least one embodiment, LIDAR sensor(s) 664 may operate at functional safety level ASIL B. In at least one embodiment, vehicle 600 may include multiple LIDAR sensors 664 (e.g., two, four, six, etc.) that may use an Ethernet channel (e.g., to provide data to a Gigabit Ethernet switch).
Shin et al. (US 2018/0149753) disclose a multi-channel LIDAR for acquiring three-dimensional spatial information on the surrounding environment, and to provide an apparatus and a method for detecting the obstacles of a moving object based on the multi-channel LIDAR which acquires and expresses environmental information using the introduced cleaning robot system, and to provide a moving object equipped with said apparatus.
The closets prior art fail to teach the limitations of claims 1, 8 and 15, e.g. “initiate optimization of a pipeline processing a signal corresponding to the emitted pulse received at a detector of the LiDAR sensor; construct a max-rank loss scalarization for the signal using the optimized pipeline; compute transients using centroid weights based upon the max-rank loss scalarization; and replace a centroid based upon a covariance matrix adaptation-evolution strategy (CMA-ES) upon determining a new centroid corresponding to the computed transients”.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
a) Parikh et al. (US 2024/0428596) disclose the 3D part of the cost function may use one or more features. For example, a position (or range) difference may be used. To account for varying track and measurement uncertainties, scaling may be used. One option for scaling may be to use the uncertainty of the prediction and the measurement noise—e.g., by using a Mahalanobis distance. Another option for scaling is to use the method described herein with respect to gating. The azimuth difference (e.g., in rig coordinates) is another feature that may be used for the 3D part of the cost function. Scaling may be used for the Azimuth difference as well.
b) Westman et al. (US 2024/0242369) disclose As will be described in greater detail, AV 102a may be configured with a lidar system, e.g., lidar system 264 of FIG. 2. The lidar system may be configured to transmit a light pulse 104 to detect objects located within a distance or range of distances of AV 102a. Light pulse 104 may be incident on one or more objects (e.g., AV 102b) and be reflected back to the lidar system. Reflected light pulse 106 incident on the lidar system may be processed to determine a distance of that object to AV 102a. The reflected light pulse may be detected using, in some embodiments, a photodetector or array of photodetectors positioned and configured to receive the light reflected back into the lidar system. Where k is the number of point neighbors considered in the neighborhood of p.sub.i, p is the 3D centroid of the nearest neighbors, λ.sub.j is the j-th eigenvalue of the covariance matrix, and v.sub.j is the j-th eigenvector of the covariance matrix.
c) Pavone et al. (US 2024/0199068) disclose SoC(s) 604 may be used to process data from cameras (e.g., connected over Gigabit Multimedia Serial Link and Ethernet channels), sensors (e.g., LIDAR sensor(s) 664, RADAR sensor(s) 660, etc. that may be connected over Ethernet channels), data from bus 602 (e.g., speed of vehicle 600, steering wheel position, etc.), data from GNSS sensor(s) 658 (e.g., connected over a Ethernet bus or a CAN bus), etc. In at least one embodiment, one or more SoC of SoC(s) 604 may further include dedicated high-performance mass storage controllers that may include their own DMA engines, and that may be used to free CPU(s) 606 from routine data management tasks. In at least one embodiment, vehicle 600 may include LIDAR sensor(s) 664. In at least one embodiment, LIDAR sensor(s) 664 may be used for object and pedestrian detection, emergency braking, collision avoidance, and/or other functions. In at least one embodiment, LIDAR sensor(s) 664 may operate at functional safety level ASIL B. In at least one embodiment, vehicle 600 may include multiple LIDAR sensors 664 (e.g., two, four, six, etc.) that may use an Ethernet channel (e.g., to provide data to a Gigabit Ethernet switch).
d) Shin et al. (US 2018/0149753) disclose a multi-channel LIDAR for acquiring three-dimensional spatial information on the surrounding environment, and to provide an apparatus and a method for detecting the obstacles of a moving object based on the multi-channel LIDAR which acquires and expresses environmental information using the introduced cleaning robot system, and to provide a moving object equipped with said apparatus.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMAD K ISLAM whose telephone number is (571)270-0328. The examiner can normally be reached M-F 9:00 a.m. - 5:00 p.m..
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A Turner can be reached at 571-272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMMAD K ISLAM/Primary Examiner, Art Unit 2857
