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 .
Status of Claims
The following is a non-final, first office action in response to the communication filed
02/06/2026. Claims 14-26 are currently pending and have been examined.
Information Disclosure Statement
Both information disclosure statements (IDS) submitted on 06/01/2023 are in compliance with the provisions of 37 CFR 1.97. Accordingly, both of the information disclosure statements are being considered by the examiner.
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.
Claims 14 and 19 through 26 are rejected under 35 U.S.C. 102(a1) as being anticipated by Steinberg, Amit et al. (US-20180113200-A1; hereinafter, Steinberg).
Regarding claim 14, Steinberg discloses (Previously Presented) A method (see at least Figure 7), comprising: receiving, using at least one processor, data characterizing detection of a target by a LiDAR sensor, (see at least [007]; "Consistent with a disclosed embodiment, a LIDAR system may include at least one processor configured to:... use first detected reflections associated with a scan of a first portion of the field of view to determine an existence of a first object in the first portion at a first distance.)" wherein the target is located within a field of view of detection of the sensor, and (see at least [007]; "Consistent with a disclosed embodiment, a LIDAR system may include at least one processor configured to:... use first detected reflections associated with a scan of a first portion of the field of view to determine an existence of a first object in the first portion at a first distance.)" wherein the target and the sensor are coupled to or adjacent to a portion of the vehicle; (see at least Figure 1A and [0123]; "In some embodiments, LIDAR system100 may include one or more scanning units104to scan the environment around vehicle110. LIDAR system100 may be attached or mounted to any part of vehicle110.") determining, using the at least one processor, a modified field of view of the sensor, (see at least [0734]; "In some embodiments, processor118 may identify a region of interest in a portion of the FOV and modify, based on the temperature information, the illumination ratio between the portion of the FOV and another portion of the FOV such that during one or more subsequent scanning cycles, more light is directed toward the portion of the FOV containing a region of interest.") wherein the modified field of view is narrower than the field of view, and (see at least [0112]; "for a scanning LIDAR system, the instantaneous field of view is narrower than the entire FOV of the LIDAR system, and it can be moved within the FOV of the LIDAR system in order to enable detection in other parts of the FOV of the LIDAR system.") wherein the determining is based on at least identifying one or more regions in the field of view that include the target; and (see at least [010]: "Consistent with a disclosed embodiment, a LIDAR system may include at least one processor configured to: obtain an identification of at least one distinct region of interest in the field of view; and increase light allocation to the at least one distinct region of interest relative to other regions, such that following a first scanning cycle, light intensity in at least one subsequent second scanning cycle at locations associated with the at least one distinct region of interest is higher than light intensity in the first scanning cycle at the locations associated with the at least one distinct region of interest.") providing, using the at least one processor, a calibration dataset that includes data associated with the modified field of view. (see at least [0193]; "In one example, processor118C may be the vehicle controller and may have a shared interface between first processor118A and second processor118B." and see at least [0540]; "According to some embodiments, the controller may include a situational assessment unit to receive the detected scene signal and produce a scanning/work plan... The situational assessment unit may receive information stored on a memory. Optionally, the information may be selected from the following list... calibration data." and see at least [0734]; "In some embodiments, processor118 may identify a region of interest in a portion of the FOV and modify, based on the temperature information, the illumination ratio between the portion of the FOV and another portion of the FOV such that during one or more subsequent scanning cycles, more light is directed toward the portion of the FOV containing a region of interest.")
Regarding claim 19, Steinberg discloses (Previously Presented) The method of claim 18, wherein the at least a portion of the field of view includes a portion of the field of view overlapping the vehicle. (see at least [0518]; "In one example, a region of interest based on a sensed current driving mode may include a one or more portions of a LIDAR FOV overlapping an area that a host vehicle is turning toward (as conveyed by navigation system2910, GPS receiver2908, etc.).")
Regarding claim 20, Steinberg discloses (Previously Presented) The method of claim 14, further comprising conforming the target to the portion of the vehicle. (rejected for same reasons as described herein from Claim 19 and see at least [0518]; "In another example, a region of interest may correspond to one or more portions of a LIDAR FOV in which LIDAR system100 has detected an object, such as another vehicle, a pedestrian, obstacle, etc.")
Regarding claim 21, Steinberg discloses (Previously Presented) The method of claim 14, wherein the LiDAR sensor has a 360 degree field of view. (see at least [0123]; "Thus, LIDAR system100 may have a 360-degree horizontal field of view. In one example, as shown in Fig. IA, LIDAR system100 may include a single scanning unit104 mounted on a roof vehicle110.")
Regarding claim 22, Steinberg discloses (Previously Presented) The method of claim 14, wherein the target includes at least a first region of high reflectivity and a second region of low reflectivity. (see at least [0509]; "A computational budget may also be apportioned relative to calculations associated with a particular LIDAR FOV such that computational tasks associated with one portion of the FOV may receive more of the computation budget than computational tasks associated with another portion of the FOV. Some examples of how a computation budget may be apportioned include, for example: detection/clustering (object level from point cloud points); determining object characteristics (e.g., size, direction, velocity, reflectivity, etc.).")
Regarding claim 23, Steinberg discloses (Previously Presented) The method of claim 14, wherein providing the calibration data set comprises providing instructions for the LiDAR sensor to generate a point cloud based on the modified view. (see at least [0540]; "According to some embodiments, the controller may include a situational assessment unit to receive the detected scene signal and produce a scanning/work plan... The situational assessment unit may receive information stored on a memory. Optionally, the information may be selected from the following list:... calibration data." and see at least [0124]; "In one embodiment, LIDAR system100 may generate a plurality of point-cloud data entries from detected reflections of multiple scanning cycles of the field of view to enable, for example, determining a point cloud model of the environment around vehicle110.")
Regarding claim 24, Steinberg discloses (Previously Presented) The method of claim 14, wherein determining the calibration data set comprises pre-processing, using the at least one processor, a point cloud corresponding to the field of view. (see at least [0540]; "According to some embodiments, the controller may include a situational assessment unit to receive the detected scene signal and produce a scanning/work plan... The situational assessment unit may receive information stored on a memory. Optionally, the information may be selected from the following list:... calibration data." and see at least [0124]; "In one embodiment, LIDAR system100 may generate a plurality of point-cloud data entries from detected reflections of multiple scanning cycles of the field of view to enable, for example, determining a point cloud model of the environment around vehicle110.")
Regarding claim 25, Steinberg discloses (Currently Amended) A system (see at least Figure 1A.) comprising: at least one computer-readable medium storing computer-executable instructions; (see at least [0129]; "In this figure, LIDAR system100 is connected to a host210. Consistent with the present disclosure, the term "host" refers to any computing environment that may interface with LIDAR system100, it may be a vehicle system (e.g., part of vehicle110), ... , or any system that monitors its surroundings." and see at least [0443]; "Referring to method2400 as a whole, and to any variation of which is discussed above, it is noted that method2400 may be embodied into a computer readable code (a set of instructions) which can be executed by a processor (e.g. a controller of a LIDAR).") one or more processors configured to execute the computer executable instructions comprising: (see at least [0443]; "That non-transitory computer-readable medium may include instructions stored thereon, that when executed on a processor, may perform steps including: (a) obtaining preliminary detection-information of light emitted by the LIDAR during the respective frame-time and reflected from the respective segment; and (b) selectively controlling, based on the preliminary detection- information, subsequent emission of light by the LIDAR to the respective segment during the respective frame-time.")…
The remainder of claim 25 contains analogous limitations to claim 14 and is rejected for similar reasons.
Regarding claim 26, Steinberg discloses (Currently Amended) A non-transitory computer-readable storage medium, (see at least Figure 1A and [0443]; “That non-transitory computer-readable medium may include instructions stored thereon, that when executed on a processor; it is noted that method2400 may be embodied into a computer readable code (a set of instructions) which can be executed by a processor (e.g. a controller of a LIDAR).”) comprising at least one program for execution by one or more processors of a first device, (see at least [0443]; "That non-transitory computer-readable medium may include instructions stored thereon, that when executed on a processor, may perform steps including: (a) obtaining preliminary detection-information of light emitted by the LIDAR during the respective frame-time and reflected from the respective segment; and (b) selectively controlling, based on the preliminary detection- information, subsequent emission of light by the LIDAR to the respective segment during the respective frame-time.") the at least one program including instructions which, when executed by the one or more processors, cause the first device to perform the steps of: (see at least [0443]; "Referring to method2400 as a whole, and to any variation of which is discussed above, it is noted that method2400 may be embodied into a computer readable code (a set of instructions) which can be executed by a processor (e.g. a controller of a LIDAR).")…
The remainder of claim 26 contains analogous limitations to claim 14 and is rejected for similar reasons.
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.
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.
Claims 15 through 18 are rejected under 35 U.S.C. 103 as being unpatentable by Steinberg and Cai, Zhongping et al. (US-20210325520-A1; hereinafter, Cai)
Regarding claim 15, Steinberg discloses [Note: what Steinberg fails to disclose is strike-through] (Previously Presented) The method of claim 14, wherein determining the modified field of view comprises: identifying, based on the data characterizing detection of the target, a wherein the between the target and (see at least [0734]; "In some embodiments, processor118 may identify a region of interest in a portion of the FOV and modify, based on the temperature information, the illumination ratio between the portion of the FOV and another portion of the FOV such that during one or more subsequent scanning cycles, more light is directed toward the portion of the FOV containing a region of interest." and see at least [0111]; "The field of view of LIDAR system may be 15defined,or example, by a solid angle (e.g. defined using 0,0 angles, in which 0 and 0 are angles defined in perpendicular planes, e.g. with respect to symmetry axes of the LIDAR system and/or its FOV).") the portion of the vehicle, wherein the calibration dataset includes the (see at least [0540]; "According to some embodiments, the controller may include a situational assessment unit to receive the detected scene signal and produce a scanning/work plan... The situational assessment unit may receive information stored on a memory. Optionally, the information may be selected from the following list:... calibration data." and see at least [0124]; "In addition to location, each gray dot may also be associated with different types of information, for example, intensity (e.g., how much light returns back from that location), reflectivity, proximity to other dots, and more. In one embodiment, LIDAR system100 may generate a plurality of point-cloud data entries from detected reflections of multiple scanning cycles of the field of view to enable, for example, determining a point cloud model of the environment around vehicle110.").
However, Steinberg does not explicitly teach how to identify a calibration azimuth angle. Instead, Steinberg teaches how to modify the field of view, determine an environment around the vehicle using point-cloud data, and define a field of view with a solid angle.
Steinberg discloses a method to generate field of view data using angles and calibration data from the processor, and Cai is directed at evaluating data via a calibration module to generate azimuths. Cai teaches:
Calibration azimuth angle, (see at least [00125]; “the calibration module may use the environmental data E to determine the azimuths (horizontal) from the LiDAR device 512 to each of the reflective panels, and may control each of the channels 102 of the LiDAR device 512 to emit light signals along each of those azimuths. Some examples of techniques for controlling the channels 102 of a LiDAR device to emit light signals along particular azimuths are described above.”)
Both Steinberg and Cai can define LiDAR with calibration data and angles. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method used in Steinberg to include calibration azimuth angle data as taught by Cai. The calibration module taught by Cai includes environmental data to determine azimuths and Steinberg teaches its controller to have a situational assessment unit that can receive information stored on memory which can be calibration data. One of ordinary skill would be motivated to include calibration azimuth data with the calibration data as it is generated in the situational assessment unit. Therefore, the calibration azimuth angle can be automatically generated from the calibration data set by having the situational assessment unit calculate it from the determining data set for the modified field of view and associate this angle between the target and the portion of the vehicle.
Regarding claim 16, Steinberg discloses [Note: what Steinberg fails to disclose is strike-through] (Previously Presented) The method of claim 15, wherein identifying the (see at least [0124]; "In addition to location, each gray dot may also be associated with different types of information, for example, intensity (e.g., how much light returns back from that location), reflectivity, proximity to other dots, and more. In one embodiment, LIDAR system100 may generate a plurality of point-cloud data entries from detected reflections of multiple scanning cycles of the field of view to enable, for example, determining a point cloud model of the environment around vehicle110.") wherein the beam is generated by the sensor. (see at least [0112]; "The movement of the instantaneous field of view within the FOV of the LIDAR system may be achieved by moving a light deflector of the LIDAR system (or external to the LIDAR system), so as to deflect beams of light to and/or from the LIDAR 25system idiffering directions.")
However, Steinberg does not explicitly teach how to identify a calibration azimuth angle from point-cloud data. Instead, Steinberg teaches reflectivity of a beam between the target and the portion of the vehicle from a plurality of point-cloud data entries.
Steinberg discloses a method to use point-cloud data to measure reflectivity from data generated by the LiDAR system, and Cai is directed at evaluating data via a calibration module to generate azimuths. Cai teaches:
Calibration azimuth angle, (see at least [00125]; “the calibration module may use the environmental data E to determine the azimuths (horizontal) from the LiDAR device 512 to each of the reflective panels, and may control each of the channels 102 of the LiDAR device 512 to emit light signals along each of those azimuths. Some examples of techniques for controlling the channels 102 of a LiDAR device to emit light signals along particular azimuths are described above.”)
Both Steinberg and Cai evaluate data in response to received data from their LiDAR systems. It would have been obvious for one skilled in the art before the effective filing date of the claimed invention to modify the method used in Steinberg to include calibration azimuth angle data as taught by Cai. The calibration module taught by Cai includes environmental data to determine azimuths and point-cloud data entries can be generated from the LiDAR system as taught by Steinberg. One of ordinary skill would be motivated to calculate calibration azimuth data with the point-cloud data as it is generated by the LiDAR system. Therefore, the calibration azimuth angle can be automatically generated from the point-cloud data set by having the LiDAR system calculate it from the point-cloud data set of the field of view.
Regarding claim 17, Steinberg discloses [Note: what Steinberg fails to disclose is strike-through] (Previously Presented) The method of claim 16, further comprising generating the data characterizing detection of the target, (see at least [007]; "Consistent with a disclosed embodiment, a LIDAR system may include at least one processor configured to:... use first detected reflections associated with a scan of a first portion of the field of view to determine an existence of a first object in the first portion at a first distance.") wherein the generating includes:directing the beam from the sensor at a plurality of (see at least [0223]; "For example, method700 may include generating output data (e.g., a 3D model) in which the differing measurements are associated with different directions with respect to the LIDAR. In such an example, processor118 may create a 3D-model frame (or the like) from the information of different light beams and many pixels from different angles of the FOV.") detecting reflection of at least a portion of the beam. (see at least [0109]; "For example, in some cases, light may be reflected from only some sides of the object (e.g., only the side opposing the LIDAR system will be detected); in other cases, light may be projected on only part of the object (e.g. laser beam projected onto 30a road oa building); in other cases, the object may be partly blocked by another object between the LIDAR system and the detected object; in other cases, the LIDAR's sensor may only detects light reflected from a portion of the object, e.g., because ambient light or other interferences interfere with detection of some portions of the object.")
However, Steinberg does not explicitly teach how to identify an azimuth angle. Instead, Steinberg teaches generating angles from a 3D model frame generated by the processor.
Steinberg discloses a method to use detected reflections to detect a target within its field of view and object detection of part of the LiDAR due to interference, and Cai is directed at evaluating data via a calibration module to generate azimuths. Cai teaches:
Azimuth angle, (see at least [00125]; “the calibration module may use the environmental data E to determine the azimuths (horizontal) from the LiDAR device 512 to each of the reflective panels, and may control each of the channels 102 of the LiDAR device 512 to emit light signals along each of those azimuths. Some examples of techniques for controlling the channels 102 of a LiDAR device to emit light signals along particular azimuths are described above.”)
Both Steinberg and Cai evaluate data and angles generated by their LiDAR systems. It would have been obvious for one skilled in the art before the effective filing date of the claimed invention to modify the method used in Steinberg to include azimuth angle data as taught by Cai. The calibration module taught by Cai includes environmental data to determine azimuths and output data from a 3D model as taught by Steinberg already contains information on different angles. One of ordinary skill would be motivated to calculate azimuth data from the plurality of different angles produced of the field of view from the 3D model with respect to the LiDAR. Therefore, a plurality of azimuth angles can be automatically generated from the 3D model generated with respect to the LiDAR sensor’s processor.
Regarding claim 18, Steinberg discloses [Note: what Steinberg fails to disclose is strike-through] (Previously Presented) The method of claim 15, further comprising:receiving, by the sensor, data representing the (see at least [0734]; "In some embodiments, processor118 may identify a region of interest in a portion of the FOV and modify, based on the temperature information, the illumination ratio between the portion of the FOV and another portion of the FOV such that during one or more subsequent scanning cycles, more light is directed toward the portion of the FOV containing a region of interest." and see at least [0223]; "For example, method700 may include generating output data (e.g., a 3D model) in which the differing measurements are associated with different directions with respect to the LIDAR. In such an example, processor118 may create a 3D-model frame (or the like) from the information of different light beams and many pixels from different angles of the FOV.")
However, Steinberg does not explicitly teach how to modify a field of view using a calibration azimuth angle. Instead, Steinberg teaches modifying fields of view using other information, for example: illumination and temperature, and generating angles from a 3D model frame generated by the processor.
Steinberg discloses a method to generate data into a 3D model representation to produce data which one facet is angles, and Cai is directed at evaluating data via a calibration module to generate azimuths. Cai teaches:
Calibration azimuth angle, (see at least [00125]; “the calibration module may use the environmental data E to determine the azimuths (horizontal) from the LiDAR device 512 to each of the reflective panels, and may control each of the channels 102 of the LiDAR device 512 to emit light signals along each of those azimuths. Some examples of techniques for controlling the channels 102 of a LiDAR device to emit light signals along particular azimuths are described above.”)
Both Steinberg and Cai evaluate data in response to received data from their LiDAR systems. It would have been obvious for one skilled in the art before the effective filing date of the claimed invention to modify the method used in Steinberg to include calibration azimuth angle data as taught by Cai. The calibration module taught by Cai includes environmental data to determine azimuths and output data from a 3D model as taught by Steinberg already contains information on different angles. One of ordinary skill would be motivated to calculate azimuth data from the 3D model with respect to the LiDAR sensor. Therefore, the LiDAR’s processor can identify regions of interest in a field of view and modify the field of view based on calibration azimuth angle data.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Mark A. Flores whose telephone number is (571)272-9693. The examiner can normally be reached Mon-Thurs 7:30am-5:30pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vladimir Magloire can be reached at (571)270-5144. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MARK ANTHONY FLORES/Examiner, Art Unit 3648
/VLADIMIR MAGLOIRE/Supervisory Patent Examiner, Art Unit 3648
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