Ground or obstacles? Detecting clear paths in vehicle navigation

Abstract

Efficient estimation of obstacles is a crucial component in autonomous vehicle navigation. Fusing stereo vision and laser scan data is a widely used approach for obstacle detection and navigation. Stereo vision can detect obstacles and the ground. Planar laser range finders can detect obstacles, but false positives occur when the scans collide with the ground. This paper proposes an algorithm for cooperative fusion of stereo vision and laser data. The algorithm checks the consensus of the two signals before filtering out the false positive laser scans from ground hits. Experimental results for tests in real driving situations in an industrial environment are presented. The results confirm the effectiveness of the proposed algorithm for robust and safe navigation.