Visually-guided obstacle avoidance

Abstract

The paper describes an indoor autonomous vision based obstacle avoidance robot system. The vision part of the system converts forward looking greyscale camera images into edge images using Canny edge detection. Both edge image and sonar ranging information is used as stimuli by the behaviours that make up the reactive part of the system. These behaviours all run concurrently and they couple perception to actions to generate motor responses. A priority based subsumption coordinator selects the most appropriate response to direct the robot away from obstacles.