Navigation and control of a mobile robot among moving obstacles

The issues related to navigation and control of a mobile robot which enable it to deal with unexpected moving obstacles by sensor-based control are addressed. A probabilistic approach to deal with collision avoidance under uncertainty is proposed. It is assumed that the uncertainties both in the position of a moving obstacle and the error of the measurements are normally distributed. The mean and variance of the distribution are determined by a recursive Kalman filter both from a priori information and the available sensor data. The authors define a safe circle for the robot and bound a high-confidence position error ellipse of the moving obstacles. Collisions can be avoided by controlling the speed and steering of the mobile robot along the preplanned path to keep the safe circle from intersecting the ellipse. A local robot frame was chosen for collision judgement and avoidance control