Planning with Pinch Points
CARNEGIE-MELLON UNIV PITTSBURGH PA ROBOTICS INST
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We describe a heuristic search algorithm for generating optimal plans in a new class of decision problem, characterized by the incorporation of hidden state. The approach exploits the nature of the hidden state to reduce the state space by orders of magnitude. It then interleaves AO-type heuristic expansion of the reduced space with forwards and backwards propagation phases to produce a solution in a fraction of the time required by other techniques. Results are provided on an outdoor path planning application.