DocumentCode :
3181083
Title :
Support Vector Path Planning
Author :
Miura, Jun
Author_Institution :
Dept. of Mech. Eng., Osaka Univ.
fYear :
2006
fDate :
9-15 Oct. 2006
Firstpage :
2894
Lastpage :
2899
Abstract :
This paper describes a unique approach of applying a pattern classification technique to robot path planning. A collision-free path connecting a start and a goal point provides information on the division of the space. In the case of 2D path planning, for example, the path divides the space into two regions. This suggests a dual problem of first dividing the whole space into such two regions and then picking up the boundary as a path. We develop a method of solving this dual problem using support vector machine (SVM). SVM generates a nonlinear separating surface based on the margin maximization principle. This property is suitable for the purpose of usual path planning problems, that is, generating a safe and smooth path. The details of the path planning methods in 2D and 3D spaces are described with several planning results. Future possibilities of combining the proposed concept with other path planning methodologies are also discussed
Keywords :
collision avoidance; maximum principle; mobile robots; support vector machines; nonlinear separating surface; pattern classification technique; robot path planning; support vector machine; support vector path planning; Intelligent robots; Joining processes; Mechanical engineering; Object recognition; Orbital robotics; Path planning; Pattern classification; Pattern recognition; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0258-1
Electronic_ISBN :
1-4244-0259-X
Type :
conf
DOI :
10.1109/IROS.2006.282140
Filename :
4058834
Link To Document :
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