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Carnegie Mellon Robotics Institute

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Abstract

Inverse kinematics is computationally expensive and can result in significant control delays in real time. For a redundant robot, additional computations are required for the inverse kinematic solution through optimization schemes. Based on the fact that humans do not compute exact inverse kinematics, but can do precise positioning for heuristics, an inverse kinematic mapping using fuzzy logic is developed. The implementation of the scheme has demonstrated that it is feasible for both redundant and nonredundant cases, and that it is very computationally efficient. The result provides sufficient precision, and transient tracking error can be controlled based on a fuzzy adaptive scheme proposed in the paper.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Text Reference

Yangsheng Xu and Michael Nechyba, "Fuzzy Inverse Kinematic Mapping: Rule Generation, Efficiency and Implementation," Proceedings of International Conference on Intelligent Robots and Systems, July, 1993, pp. 911 - 918.

BibTeX Reference

@inproceedings{Xu_1993_1404,
   author = "Yangsheng Xu and Michael Nechyba",
   title = "Fuzzy Inverse Kinematic Mapping: Rule Generation, Efficiency and Implementation",
   booktitle = "Proceedings of International Conference on Intelligent Robots and Systems",
   pages = "911 - 918",
   month = "July",
   year = "1993",
   volume = "2",
}

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