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Obstacle avoidance for autonomous land vehicle navigation in indoor environments by quadratic classifier

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題名: Obstacle avoidance for autonomous land vehicle navigation in indoor environments by quadratic classifier

作者: C. H. Ku;W. H. Tsai

貢獻者: Department of Information Communication

關鍵詞: ALV navigation;collision-free path;computer vision;obstacle avoidance;obstacle detection;pattern recognition;quadratic classifier

日期: 1999

上傳時間: 2009-11-25T02:31:09Z 出版者: Asia University

摘要: A vision-based approach to obstacle avoidance for autonomous land vehicle (ALV) navigation in indoor environments is proposed. The approach is based on the use of pattern recognition scheme, the quadratic classifier, to find collision-free paths in unknown indoor corridor environments. Obstacles treated in this study include the walls of the corridor and the objects that appear in the way of ALV navigation in the corridor. Detected obstacles as well as the two sides of the ALV body are

considered as patterns. A systematic method for separating these patterns into two classes is proposed. The two pattern classes are used as the input data to design a quadratic classifier. Finally, the two-dimensional decision boundary of the classifier, which goes through the middle point between the two front vehicle wheels, is taken as a local collision-free path. This approach is implemented on a real ALV and successful navigations confirm the feasibility of the approach.

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