Probabilistic Uncertainty Modeling of Obstacle Motion for Robot Motion Planning
Jun Miura and Yoshiaki Shirai
Dept. of Computer-Controlled Mechanical Systems, Osaka University, Suita, Osaka, 565-0871 Japan
This paper describes a method of modeling the motion uncertainty of moving obstacles and its application to mobile robot motion planning. The method explicitly considers three sources of uncertainty: path ambiguity, velocity uncertainty, and observation uncertainty. In the uncertainty model, the position of an obstacle at a certain time point is represented by a probabilistic distribution over possible positions on each possible path of the moving obstacle. Using this model, the best robot motion is selected in a decision-theoretic way. By considering the distribution, not the range, of uncertainty, more efficient behavior of the robot is realized.
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