). Local potential field approaches usually suffer from local minima problems. Another problem of the navigation function approaches is falling into a loop. The sensory information is inherently local, and the same action will be always taken for the same local situation, without any global considerations. Therefore once trapped in a loop, there is no way t o get out of it. A different approach, which guarantees reaching the target if possible, was presented by Lumelsky and Stepanov [7] . The robot, equipped only with contact sensors, goes straight to the target until hitting an obstacle. It then follows the object boundary. The algorithms define "leaving conditions" that determine where to leave the obstacle boundary and go directly towards the target again. The convergence is based on the fact that the distance from every leave point t o the target is strictly smaller than the distance from the corresponding hit point. Algorithms that use only the direction t o the target and abandon obstacles as soon as possible were presented in [lo] and [8]. Range sensing was used in [6] t o find "shortcuts" t o the path that would be planned using contact sensors. We will present a new algorithm DistBug that uses range information more effectively. The main contribution is a new "leaving condition" that allows the robot t o abandon obstacles as soon as global convergence is guaranteed, based on the free range in the direction to the target. Range data is utilized for choosing the turning direction when the robot approaches an obstacle. A criterion for reversing the boundary following direction when it seems t o be the wrong direction is also introduced. As a direct result of these local decisions, a significant improvement in the performance was achieved. We consider a point robot that moves among arbitrary obstacles in a planar environment. We assume that the workspace is bounded. It follows directly that the perimeter of any obstacle is finite, and that the number of obstacles is finite. The rest of the paper is organized as follows: Sec-
The method of Kamon and Rivlin REF relies on range data to make local decisions and the condition for leaving the obstacle boundary is based on the free range in the direction to the target.
Sensory based motion planning with global proofs
Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots
Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots
Computer Science