Formulation of planning of vision and motion for a mobile robot under uncertainty

A formulation for planning of vision and motion for a mobile robot under uncertainty is described. For planning in the real world, uncertainty and the cost of visual recognition are important issues. A robot has to consider a tradeoff between the cost of visual recognition and the effect of information obtained by recognition. One problem is to generate a sequence of vision and motion operations based on sensor information which is an integration of the current information and the predicted next sensor data. The problem is formulated by using statistical decision theory. A solution is obtained by recursive prediction of sensor information and the recursive search of operations. Using the framework, a robot can successfully generate a vision-motion plan