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The capability of real-time obstacle avoidance is essential for safe operation of the mobile robots in a dynamically changing environment. This paper investigates how a car-like mobile robot handles unexpected static obstacles while following an optimal path planned by the global path planner. To find an optimal solution of the problem, the obstacle avoidance problem is formulated as a decision theoretic approach. The optimal decision rule we seek is to minimize the Bayes risk by trading off between deliberative maneuver and the alternatives. Real-time implementation is emphasized here to provide a framework for real world applications.


Conference paper

Publication Date



1457 - 1464