Abstract
Performing complex assembly tasks with robots requires fine-motion planners able to cope with uncertainty and contact motions, and this is a recognized difficult issue. This paper proposes a method to predict the behavior of motions under contact uncertainty in order to check the feasibility of paths generated by gross-motion planning algorithms from a nominal model of the environment. This pragmatical approach enables the extension of gross-motion planning techniques to constrained-motion planning problems, ensuring the feasibility of the task despite the uncertainties. The approach has been implemented for assembly tasks in the plane with three degrees of freedom.
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