Abstract: For multi-robot coordination experiments, traditional algorithmic approaches through partial optimization methods have given incomplete solutions with very heavy computational burdens. Complete neural-fuzzy solutions are still in exploratory stages, and are yet to be worked out. This paper addresses problems of planning coordinated robot motions by applying 3D measurement of human arm motions. This paper then proposes an improved fuzzy expert controller which executes optimally-planned paths given by the coordinated-motion planner. This fuzzy controller consists of a rule-based fuzzy tuner and intermittent algorithmic optimizer.!12
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