In this paper, a multi-sensor fusion based environment perception architecture for ground unmanned vehicles is proposed. The target-level multi-sensor fusion technology is presented to take advantages of camera and millimeter wave (MMW) radar in target perception. On this basis, a multi-target tracking model is designed to solve the problems of alignment, association, uncertainty, as well as the elimination of false data. In order to verify the stability and real-time performance of the proposed algorithm, a real vehicle test was implemented according to the statistical data and relevant indicators. The results show that the proposed algorithm can effectively perceive and track multiple obstacles in real scene.
Radar and Camera Fusion based Moving Obstacle Tracking for Automated Vehicles
29.10.2021
2865587 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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