Author:
Guo Xiaoxiao,Liu Yuansheng,Zhong Qixue,Chai Mengna, ,
Abstract
Multi-sensor fusion and target tracking are two key technologies for the environmental awareness system of autonomous vehicles. In this paper, a moving target tracking method based on the fusion of Lidar and binocular camera is proposed. Firstly, the position information obtained by the two types of sensors is fused at decision level by using adaptive weighting algorithm, and then the Joint Probability Data Association (JPDA) algorithm is correlated with the result of fusion to achieve multi-target tracking. Tested at a curve in the campus and compared with the Extended Kalman Filter (EKF) algorithm, the experimental results show that this algorithm can effectively overcome the limitation of a single sensor and track more accurately.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
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