Application of a blind person strategy for obstacle avoidance with the use of potential fields

Abstract

This paper proposes a new obstacle avoidance algorithm for the CONTROLAB AGV which uses a similar strategy adopted by a blind person to avoid obstacles while walking. The AGV moves within an office environment with a known floorplan and uses an electronic stick consisting of infrared sensors to detect unknown obstacles. Initially, a global potential field function is defined for each floorplan room. While the AGV is moving the original potential function is modified each time an obstacle is detected by the infrared sensors. This modification is simply performed by the addition of previously calculated potential field values on a grid which represents the room working area. The interesting aspects of the proposed approach are that the potential function adaptation involves very low computational burden, the algorithm is free from local minima, the obstacles can have any shape and low cost sensors can be used to detect obstacles.