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Learning error-recovery strategies in telerobotic systems

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2 Author(s)
Zheng, Y. ; McGill Res. Centre for Intelligent Machines, McGill Univ., Montreal, Que., Canada ; Daneshmend, L.K.

The reduction of the dependence of the autonomous system on the human operator when recovering from error states is addressed. The focus is on the problem of formulating error recovery strategies, rather than that of the overall planning of complex tasks. A novel approach that utilizes explanation-Xased learning as a framework for the acquisition of error recovery knowledge is presented

Published in:

Robotics and Automation, 1991. Proceedings., 1991 IEEE International Conference on

Date of Conference:

9-11 Apr 1991