Planning with Uncertainty in Position: an Optimal Planner
CARNEGIE-MELLON UNIV PITTSBURGH PA ROBOTICS INST
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We propose a resolution-optimal planner that considers uncertainty while optimizing any monotonic objective function such as mobility cost, risk, energy expended, etc. The resulting path is a one that minimizes the expected cost value of the objective function, while ensuring that the uncertainty in the position of the robot does not compromise the safety of the robot or the reachability of the goal.