Skill based motion planning in hierarchical intelligent control of a redundant manipulator

This paper introduces a skill based manipulation in a hierarchical intelligent control scheme for robots. The scheme has three levels: learning level, skill level and adaptation level. Particularly, this paper concerns the skill level and proposes a modeling method of criteria of skilled operators for motion planning of a redundant manipulator. The method employs Fuzzy-ID3 to extract important factors from the criteria. Then it applies a genetic algorithm to optimize redundancy of the manipulator. The proposed method reduces the operator's labor and time for task teaching process. Experimental results show the effectiveness of the proposed method.

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