SYSTEMS AND METHODS FOR RETRIEVAL OF POINT CLOUD DATA FROM CACHE IN RESPONSE TO TRIGGERING EVENTS

    公开(公告)号:US20240255645A1

    公开(公告)日:2024-08-01

    申请号:US18162264

    申请日:2023-01-31

    Abstract: A LIDAR system is disclosed. The LIDAR system may include at least one light source configured to project laser light toward a field of view of the LIDAR system, at least one sensor configured to detect laser light reflections from objects in the field of view of the LIDAR system, and at least one processor configured to perform operations. The processor may be configured to use the laser light reflections to generate point-cloud representations of an environment of the LIDAR system within the field of view of the LIDAR system, output navigational information based on the generated point-cloud representations to one or more processors associated with a vehicle on which the LIDAR system is mounted, and store at least some of the generated point-cloud representations in a cache memory to provide a point-cloud archive. The processor may further be configured to detect occurrence of a point-cloud archive output triggering event, in response to detection of the point-cloud archive output triggering event, collect from the cache memory two or more point clouds from the point-cloud archive that were generated within a predetermined period of time relative to the detected point-cloud archive output triggering event, and output the two or more point clouds collected from the cache memory.

    Detecting Objects Based on Reflectivity Fingerprints

    公开(公告)号:US20190318177A1

    公开(公告)日:2019-10-17

    申请号:US16456942

    申请日:2019-06-28

    Abstract: A LIDAR system for detecting a vehicle may include a processor configured to: scan a field of view (FOV) by controlling movement of at least one deflector at which at least one light source is directed; receive from at least one sensor signals indicative of light reflected from a particular object in the FOV; detect, based on time of flight in the received signals, portions of the particular object in the FOV that are similarly spaced from the light source; determine, based on the detected portions, at least a first portion having a first reflectivity corresponding to a license plate, and at least two additional spaced-apart portions corresponding to locations on the particular object other than a location of the first portion; and based on a spatial relationship and a reflectivity relationship between the first portion and the at least two additional portions, classify the particular object as a vehicle.

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