A Simplified Fuzzy-Logic Control System Approach to Obstacle Avoidance combining Stereoscopic Vision and Sonar

Abstract

Stereoscopic vision is a technique for calculating the depths of objects in a scene from two images. Ultrasonic ranging is a well-established technique for estimating the distance to objects by bouncing an acoustic pulse off the object and measuring the time-of-flight. As with any types of sensors, these techniques each have their associated strengths and weaknesses. Therefore it is desirable to be able to use both sensor types simultaneously on a robot such that the benefits of the techniques can each be taken advantage of. Effective obstacle avoidance is an important challenge in the field of robotics that is integral to achieving the goal of fully autonomous mobile robots. To achieve such behaviour a control system is required for directing the robot on the basis of sensor inputs. This study presents a simplified fuzzy logic control system that differs from the standard fuzzy logic system in the way that fuzzy sets are generated. The control layers of the system dynamically create fuzzy sets on-the-fly when called upon to do so. The developed control system is used to show that there are benefits to combining stereoscopic vision and sonar for robot obstacle avoidance compared against using these sensors in isolation.