Baidu USA LLC

Baidu.com Times Technology (beijing) Co. Ltd.

Apollo Intelligent Driving Technology (beijing) Co., Ltd.

Dongchao Gao

Fan Zhu

Fan Yang

Bin Gao

Chengfa Wang

Yongyi Sun

Junping Wang

Zelin Wu

Guohao Gong

Tiankun Zhao

Shuang Zhang

A method, apparatus, and system for filtering a point cloud generated by a LIDAR device in an autonomous vehicle is disclosed. A point cloud comprising a plurality of points is generated based on outputs of the LIDAR device. The point cloud is filtered to remove a first set of points in the plurality of points that correspond to noise based on one or more of: point intensity measurements, distances between points, or a combination thereof. Perception data is generated based on the filtered point cloud. Operations of the autonomous vehicle are controlled based on the perception data.

Neighbor-based point cloud filter system

A method, apparatus, and system for determining whether all extrinsic matrices are accurate is disclosed. A plurality of post-LIDAR fusion point clouds that are based on simultaneous outputs from a plurality of LIDAR devices installed at one ADV are obtained. The obtained plurality of point clouds are filtered to obtain a first set of points comprising all points in the plurality of point clouds that fall within a region of interest. Each point in the first set of points corresponds to one coordinate value on the axis in the up-down direction. A distribution of the first plurality of coordinate values is obtained. A quantity of peaks in the distribution of the first plurality of coordinate values is determined. Whether all extrinsic matrices associated with the plurality of LIDAR devices are accurate is determined based on the quantity of peaks in the distribution of the first plurality of coordinate values.

Detector for point cloud fusion

A method, apparatus, and system for filtering obstacle candidates determined based on outputs of a LIDAR device in an autonomous vehicle is disclosed. A point cloud comprising a plurality of points is generated based on outputs of the LIDAR device. One or more obstacle candidates are determined based on the point cloud. The one or more obstacle candidates are filtered to remove a first set of obstacle candidates in the one or more obstacle candidates that correspond to noise based at least in part on characteristics associated with points that correspond to each of the one or more obstacle candidates. One or more recognized obstacles comprising the obstacle candidates that have not been removed are determined. Operations of an autonomous vehicle are controlled based on the recognized obstacles.

Point cloud feature-based obstacle filter system

A method, apparatus, device, and medium for verifying vehicle information are provided. A specific implementation scheme is: determining a target coding precision and a target coding mode of a target data packet to be transmitted; coding the target data packet based on the target coding precision and the target coding mode, to determine target verification information of the target data packet; and transmitting the target data packet and the target verification information, to instruct a receiving-end vehicle to verify the target data packet based on the target verification information.

Method, apparatus, device, and medium for verifying vehicle information

The present disclosure provides a method for measuring a sensing range of a vehicle, a device and a medium, and relates to a technical field of automatic driving. The method includes: determining a target road side unit to be measured according to a road side unit identifier; when it is detected that the vehicle receives a road-side message from the target road side unit, determining vehicle positioning information of the vehicle when the road-side message is received; and determining a sensing range of the vehicle to the target road side unit in a target lane in which the vehicle travels according to the vehicle positioning information.

Growing community of inventors

Beijing, China

Dongchao Gao