International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Path planning of a Robot Manipulator using Retrieval RRT Strategy

  • Oh, Kyong-Sae (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Kim, Eun-Tai (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Cho, Young-Wan (Department of Computer Engineering, Seokyeong University)
  • Published : 2007.06.01
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Abstract

This paper presents an algorithm which extends the rapidly-exploring random tree (RRT) framework to deal with change of the task environments. This algorithm called the Retrieval RRT Strategy (RRS) combines a support vector machine (SVM) and RRT and plans the robot motion in the presence of the change of the surrounding environment. This algorithm consists of two levels. At the first level, the SVM is built and selects a proper path from the bank of RRTs for a given environment. At the second level, a real path is planned by the RRT planners for the: given environment. The suggested method is applied to the control of $KUKA^{TM}$, a commercial 6 DOF robot manipulator, and its feasibility and efficiency are demonstrated via the cosimulatation of $MatLab^{TM}\;and\;RecurDyn^{TM}$.

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