Stereo vision based obstacle avoidance path-planning for cross-country intelligent vehicle

Authors:
Li Linhui;Zhang Mingheng;Guo Lie;Zhao Yibing
Affiliations:
School of Automotive Engineering, Dalian University of Technology, Dalian;School of Automotive Engineering, Dalian University of Technology, Dalian;School of Automotive Engineering, Dalian University of Technology, Dalian;School of Automotive Engineering, Dalian University of Technology, Dalian
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Year:
2009

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Abstract

Intelligent vehicle navigation in complex crosscountry terrain can benefit from accurate obstacle avoidance path-planning. The paper presents an obstacle avoidance path-planning algorithm based on stereo vision system. Firstly, Multi-feature extraction based stereo matching techniques is proposed on a corner and edge extracted image pair to accomplish environmental perception, which can provide robust detection results under complex conditions. Secondly, in order to plan a path for a vehicle, a method of analyzing three-dimensional data produced by stereo vision is described. It computes estimates of interpolated height, slope, and roughness at equally spaced grids, as well as accuracy estimates of each grid. Then fuzzy rule is designed to integrate slope, roughness and certain value to analysis the traversability. To realize obstacle avoidance pathplanning for cross-country intelligent vehicle, traversability is considered in Vector Field Histogram (VFH) algorithm and obstacle avoidance behaviors are designed. Experiments confirm the effectiveness of the obstacle avoidance path-planning method.