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Collaborative planning of assembly sequences with joint intelligence

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1 Author(s)
Xiaobu Yuan ; School of Computer Science, University of Windsor, Ontario, Canada

Presented in this paper is a method that combines computer and human intelligence into a joint power to confront the intractability of assembly sequence planning. This method applies the theory of parameterized complexity to identify the source of complexity, and then separates and designates different tasks according to the strengths of autonomous planning and human reasoning for collaborative planning. The injection of human expertise via collaboration greatly helps to reduce the computational complexity of autonomous planning, and parameterized complexity analysis provides the much needed guideline for automated processes to decide when and what types of help are needed so that human intervention can be reduced to the minimum.

Published in:

Robotics and Automation (ICRA), 2011 IEEE International Conference on

Date of Conference:

9-13 May 2011