公开(公告)号：US20230056784A1

公开(公告)日：2023-02-23

申请号：US17889091

申请日：2022-08-16

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Xiao ZHANG ,  Fangfang DONG ,  Guowei WAN

IPC: G06V20/58 ,  G01S7/497 ,  B60W60/00

Abstract: The disclosure provides a method for detecting an obstacle, an electronic device, and a storage medium, relates to the field of artificial intelligence, and in particular, to the field of automatic driving. A specific implementation solution includes: acquiring point cloud data collected by a lidar sensor during detection of an obstacle; converting the point cloud data into an obstacle feature map, where the obstacle feature map includes a to-be-detected image feature, and the to-be-detected image feature includes an obstacle feature; performing feature extraction on the to-be-detected image feature in the obstacle feature map to obtain the obstacle feature, increasing a weight value in the obstacle feature map of the obstacle feature during the feature extraction, and monitoring the feature extraction based on monitoring data generated by point cloud distribution data corresponding to the point cloud data; and determining a target obstacle according to the obstacle feature.

公开(公告)号：US20230060005A1

公开(公告)日：2023-02-23

申请号：US17746936

申请日：2022-05-17

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Jianan JIANG ,  Xu LIU ,  Jinyun ZHOU ,  Fangfang DONG ,  Guowei WAN

IPC: B60W30/095 ,  B60W60/00 ,  B60W40/04 ,  B60W50/00 ,  G06N3/08

Abstract: The present disclosure provides a method and device for predicting a motion track of an obstacle and an autonomous vehicle, and relates to the technical field of autonomous driving, so as to at least solve the technical problem of low prediction precision of a motion track of an obstacle in an interaction scene. A specific implementation solution includes: environment information in a target scene, historical state information of a target obstacle and track planning information of a target vehicle are obtained, and the target obstacle is a potential interaction object of the target vehicle; and a motion track of the target obstacle is predicted based on the environment information, the historical state information and the track planning information.