Robot crowd navigation using predictive position fields in the potential function framework

A potential function based path planner for a mobile robot to autonomously navigate an area crowded with people is proposed. Path planners based on potential functions have been essentially static, with very limited representation of the motion of obstacles as part of their navigation model. The static formulations do not take into account the possibility of using predicted workspace configuration to augment the performance of the path planner. The use of an elliptical region signifying the predicted position and direction of motion of an obstacle is proposed in this paper. The repulsive potential caused by an obstacle is defined relative to this elliptical field. An analytic switch is made when the robot enters this predicted elliptical zone of the obstacle. The development of navigation functions makes it possible to design a potential-based planner which is guaranteed to converge to the target.