This work presents an approach to plan motion strategies for robotics tasks constrained by uncertainty in position, orientation, and control. Our approach operates in a (x, y, /spl theta/) configuration space and it combines two local functions: a contact-based attraction function and an exploration function. Compliant motions are used to reduce the position/orientation uncertainty. An explicit geometric model for the uncertainty is defined to evaluate the reachability of the obstacle surfaces when the robot translates in free space.

This paper presents an approach to plan robust motion strategies of a robot navigating through an environment composed of polygonal obstacles subject to geometric uncertainty constraints. The contacts of the robot against the obstacles are used to reduce its position and orientation uncertainties and to guide the robot to its goal configuration. The authors describe a motion planner based on this approach which generates both, free space motions and compliant motions (contact based motions). An explicit geometric model for the uncertainty is used to estimate the reachability of the goal and the intermediate subgoals (these are generated when the final goal is not reachable from the current robot configuration). Two functions are combined to explore the valid space : (1) a contact-based potential field function is used to generate continuous motions pulling the robot towards target attractors; (2) an exploration function is used to determine possible subgoals allowing progress towards the ultimate goal when local minima of the previous function occur.>