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Trajectory generation for human-friendly behavior of partner robot using fuzzy evaluating interactive genetic algorithm
Description
This paper deals with a human-friendly trajectory generation using an interactive genetic algorithm for a partner robot. Human evaluation is very important for generating robotic behavior, but the structure of human evaluation is not clear beforehand. Therefore, a fuzzy state-value function is used for estimating the structure of human evaluation of a trajectory candidate generated by an interactive genetic algorithm. We apply a profit sharing plan based on human evaluation to update the state-value function. Some experimental results show the effectiveness of the proposed method.
Journal
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- Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694)
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Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694) 1 306-311, 2004-03-02
IEEE
