Obstacle position identification method and device, computer equipment and storage medium

Abstract

The invention relates to an obstacle position identification method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring depth information, plane area information and main body area information corresponding to an obstacle; when the depth information, the plane area information and the main body area information are similar and consistent in matching, determining a target obstacle; acquiring preset position information corresponding to the target obstacle, and calculating distance error information between the depth information, the plane area information and the main body area information and the preset position information; calculating conditional probability distribution of the sensor observation information under the preset position information according to the distance error information; and estimating the conditional probability distribution to obtain target position information corresponding to the target obstacle. The accuracyof estimating the position of part of obstacles entering the view of the camera can be improved, so that the automatic driving performance is improved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to an obstacle intention recognition method, device, computer equipment and storage medium. Background technique [0002] With the development of artificial intelligence technology, self-driving technology has emerged. Self-driving cars rely on the cooperation of artificial intelligence, visual computing, radar, monitoring devices and global positioning systems, allowing computers to automatically and safely drive without any active human operation. Operate a motor vehicle. At present, automatic driving can be realized through sensor fusion. By using the image rear detection and depth detection including the entire rear of the vehicle, the position information of the obstacle in front in the three-dimensional space is estimated. [0003] However, current sensor fusion approaches require 2D rear end detection in images that include the entire rear end. So only when the ...

AI Technical Summary

Problems solved by technology

That is, when an obstacle partially enters the camera's field of view, the body (such as the front of the car entering the camera's field of view) or part of the rear of the car will not be used for image detection, which may result in only using the information of the depth sensor to estimate that part of the obstacle entering the camera's field of view Therefore, it is impossible to obtain the optimal estimated position of obstacles, resulting in defects in automatic driving performance.

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