Planning of vision and motion for a mobile robot using a probabilistic model of uncertainty

The authors propose a framework of unified planning of vision and motion with uncertainty. They use a probabilistic model to represent uncertainty and use statistical decision theory to make a unified plan of vision and motion. They describe a method of predicting the information acquired by a sensing operation and formulate the planning problem in a recurrence formula. They analyze vision-motion planning problem in a simple example and conclude that the combination of dynamic programming and hill-climbing is useful. Simulation results show the validity of the approach.<<ETX>>