SYSTEMS AND METHODS FOR LIDAR ATMOSPHERIC FILTERING BACKGROUND

    公开(公告)号:US20230401680A1

    公开(公告)日:2023-12-14

    申请号:US17806804

    申请日:2022-06-14

    CPC classification number: G06T5/006 G06T7/75 G06T2207/20024 G06T2207/10028

    Abstract: Systems and methods are provided for filtering atmospheric conditions from LiDAR point clouds. The method includes generating, using a LiDAR system, at least one point cloud, wherein the LiDAR system includes a processor. The method further includes, using the processor, identifying and isolating one or more ground points within a point cloud of the at least one point cloud, wherein the one or more ground points indicate a ground portion within an environment of the point cloud, filtering out the ground portion from the point cloud, generating an initial processed point cloud, identifying and isolating one or more atmospheric condition points within the initial processed point cloud, wherein the one or more atmospheric condition points indicate one or more atmospheric conditions within an environment of the processed point cloud, and filtering out the atmospheric condition points from the initial processed point cloud, generating a final processed point cloud.

    Systems and methods for controlling a vehicle using high precision and high recall detection

    公开(公告)号:US12258041B2

    公开(公告)日:2025-03-25

    申请号:US18065419

    申请日:2022-12-13

    Abstract: This disclosure provides systems and methods for controlling a vehicle. The method comprises receiving data from a set of sensors, wherein the data represents objects or obstacles in an environment of the autonomous vehicle; identifying objects or obstacles from the received data; determining multiple sets of attributes of the objects or obstacles, wherein each set of attributes of the objects or obstacles are determined based on data received by an individual sensor; determining a candidate trajectory for the autonomous vehicle based on the multiple sets of attributes of the objects or obstacles; and controlling the autonomous vehicle according to the candidate trajectory.

    SYSTEMS AND METHODS FOR CONTROLLING A VEHICLE USING HIGH PRECISION AND HIGH RECALL DETECTION

    公开(公告)号:US20240190424A1

    公开(公告)日:2024-06-13

    申请号:US18147906

    申请日:2022-12-29

    CPC classification number: B60W30/0956 B60W50/06 B60W60/001 B60W30/09

    Abstract: This disclosure provides systems and methods for detecting and tracking objects or obstacles in an environment of an autonomous vehicle. The method may include receiving data from a set of sensors, wherein the data represents objects or obstacles in an environment of the autonomous vehicle; and using a processor: generating high precision detection data based on the received data; identifying, from the high precision detection data, a set of objects that are classifiable by at least one known classifier; generating high recall detection data based on the received data; identifying from the high recall detection data a set of obstacles; and performing an operation on the high precision detection data of the objects and the high recall detection data of the obstacles, based on a status of the autonomous vehicle or based on one or more characteristics of the objects or the obstacles.

    SYSTEMS AND METHODS FOR CONTROLLING A VEHICLE BY DETECTING AND TRACKING OBJECTS THROUGH ASSOCIATED DETECTIONS

    公开(公告)号:US20240185612A1

    公开(公告)日:2024-06-06

    申请号:US18062228

    申请日:2022-12-06

    CPC classification number: G06V20/58 G06V10/762 G06V10/82

    Abstract: This disclosure provides methods and systems for dynamically detecting and tracking objects in an environment of an autonomous vehicle. In some embodiments, the method comprises: receiving image data from sensors of the autonomous vehicle, the image data comprising a plurality of images representative of objects in a field of view of the autonomous vehicle; detecting the objects in the plurality of images through an object detector; generating image embeddings for the objects detected in the plurality of images; determining similarity scores of the image embeddings of the objects that are detected in images received from two or more different sensors; identifying the objects that are detected in the images received from the two or more different sensors as a candidate object for tracking, if the objects have a similarity score of the image embeddings equal to or greater than a threshold value; and initializing a track for the candidate object.

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