Determining Specular Reflectivity Characteristics Using LiDAR

    公开(公告)号:US20240219523A1

    公开(公告)日:2024-07-04

    申请号:US18608512

    申请日:2024-03-18

    Inventor: Scott Dylewski

    CPC classification number: G01S7/4802 G01S17/93

    Abstract: A light detection and ranging (LIDAR) system for a vehicle includes one or more emitters configured to transmit light signals to an environment in which the vehicle is located; one or more detectors configured to receive return signals corresponding to the light signals being reflected back from an object in the environment; and one or more processors configured to: determine a reflectivity characteristic of the object based on reflectivity values associated with the object which are determined based on the return signals; and provide information relating to the reflectivity characteristic of the object to an autonomous vehicle control system.

    LIDAR SYSTEM
    156.
    发明公开
    LIDAR SYSTEM 审中-公开

    公开(公告)号:US20240151819A1

    公开(公告)日:2024-05-09

    申请号:US18481678

    申请日:2023-10-05

    CPC classification number: G01S7/4811 G01S7/484 G01S7/486 G01S17/89 G01S17/931

    Abstract: A LIDAR system includes a first polygon scanner, a second polygon scanner, and an optic. The first polygon scanner includes a plurality of first facets around an axis of rotation. The second polygon scanner includes plurality of second facets that are outward from the plurality of first facets relative to the axis of rotation. The optic is inward from the first polygon scanner relative to the axis of rotation. The optic is configured to output a first beam to the first polygon scanner. The first polygon scanner is configured to refract the first beam to output a second beam to the second polygon scanner. The second polygon scanner is configured to refract the second beam to output a third beam.

    LIDAR sensor system including a dual-polarization transmit and receive optical antenna

    公开(公告)号:US11927702B2

    公开(公告)日:2024-03-12

    申请号:US18099170

    申请日:2023-01-19

    CPC classification number: G01S7/499 G01S7/4816 G01S7/4863 G01S17/931

    Abstract: A light detection and ranging (LIDAR) sensor system for a vehicle includes one or more LIDAR pixels. At least one of the one or more LIDAR pixels includes a dual-polarization optical antenna, a second optical antenna, and one or more receivers. The dual-polarization optical antenna is configured to emit a transmit beam having a first polarization orientation, and detect a return beam having a second polarization orientation. The second optical antenna is offset from the dual-polarization optical antenna by a particular distance, and is configured to detect the return beam having the second polarization orientation. The one or more receivers are configured to generate one or more signals in response to detecting the second polarization orientation of the return beam.

    Systems and methods for IQ detection

    公开(公告)号:US11921219B2

    公开(公告)日:2024-03-05

    申请号:US18160836

    申请日:2023-01-27

    Abstract: A system and method for combining multiple functions of a light detection and ranging (LIDAR) system includes receiving a second optical beam generated by the laser source or a second laser source, wherein the second optical beam is associated with a second local oscillator (LO); splitting the second optical beam into a third split optical beam and a fourth split optical beam; transmitting, to the optical device, the third split optical beam and the fourth split optical beam; receiving, from the optical device, a third reflected beam that is associated with the third split optical beam and a fourth reflected beam that is associated with the fourth split optical beam; and pairing the third reflected beam with the second LO signal and the fourth reflected beam with the second LO signal.

    SENSOR DATA ANNOTATION FOR TRAINING MACHINE PERCEPTION MODELS

    公开(公告)号:US20240071060A1

    公开(公告)日:2024-02-29

    申请号:US17893838

    申请日:2022-08-23

    CPC classification number: G06V10/7788 G06V10/46 G06V10/774

    Abstract: Example aspects of the present disclosure relate to an example computer-implemented method for data annotation for training machine perception models. The example method can include (a) receiving source sensor data descriptive of an object, the source sensor data having a source reference frame of at least three dimensions, wherein the source sensor data includes annotated data associated with the object; (b) receiving target sensor data descriptive of the object, the target sensor data having a target reference frame of at least two dimensions; (c) providing an input to a machine-learned boundary recognition model, wherein the input includes the target sensor data and a projection of the source sensor data into the target reference frame; and (d) determining, using the machine-learned boundary recognition model, a bounded portion of the target sensor data, wherein the bounded portion indicates a subset of the target sensor data descriptive of the object.

    Multimodal perception simulation
    160.
    发明授权

    公开(公告)号:US11847869B1

    公开(公告)日:2023-12-19

    申请号:US18172912

    申请日:2023-02-22

    CPC classification number: G07C5/008 G06T15/06 G06T2210/21 G06T2210/61

    Abstract: A concurrent simulation of multiple sensor modalities includes identifying the multiple sensor modalities in association with a simulation scenario, determining a timeline interleaving a publishing or operating frequency of each of the multiple sensor modalities relative to each other, determining a current time interval of a sliding window in the timeline, determining a simulation segment of the simulation scenario using the current time interval of the sliding window, rendering a scene based on the simulation segment, executing a simulation to concurrently simulate the multiple sensor modalities using ray tracing in the rendered scene, and generating simulated sensor data of the multiple sensor modalities based on executing the simulation.

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