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Carnegie Mellon Robotics Institute

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Abstract

We present a method to model human operator's strategy in controlling a dynamically stabilized robot, Gyrover, which is a single-wheel gyroscopically stabilized robot. We first select the relevant state variables for training from kinematic and dynamic equations. Then, we defined a measure of the sensitivity of each of the state variables with respect to operator's control input by a sensitivity function in order to reduce the number of the state variables required in the model. We experimentally implemented the method and demonstrated that the robot can be automatically controlled using the learned human control model. The work is of significance in abstracting operator's skill for controlling a dynamically stabilized system in generating an automatic control input

Notes

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

Associated Lab(s) / Group(s): CREATE: Community Robotics, Education and Technology Empowerment and Advanced Mechatronics Lab

Associated Project(s): Gyrover

Text Reference

Yangsheng Xu, Wai-Kuen Yu, and K.W. Au, "Modeling human strategy in controlling a dynamically stabilized robot," Proceedings of the 1999 IEEE / RSJ International Conference on Intelligent Robots and Systems (IROS '99), October, 1999, pp. 507 - 512.

BibTeX Reference

@inproceedings{Xu_1999_3522,
   author = "Yangsheng Xu and Wai-Kuen Yu and K.W. Au",
   title = "Modeling human strategy in controlling a dynamically stabilized robot",
   booktitle = "Proceedings of the 1999 IEEE / RSJ International Conference on Intelligent Robots and Systems (IROS '99)",
   pages = "507 - 512",
   month = "October",
   year = "1999",
   volume = "1",
}

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