Proceedings PaperCollision Avoidance Under Uncertainty
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Reasoning with uncertainty has increasingly become an important issue in robot path planning. The injection of doubt into the knowledge of obstacle location calls for capabilities not available in the conventional path planners. This work redefines the concept of optimality within the context of an uncertainty grid and proposes a class of cost functions capable of incorporating such human-like attitudes of conservative and aggressive behavior.