Mobile robot obstacle avoidance techniques

In the last few years there has been a substantial progress in the field of robotics. Robots have replaced humans in the assistance of performing those repetitive and dangerous tasks which humans prefer not to do, or are unable to do due to size limitations, or even those such as in outer space or at the bottom of the sea where humans could not survive the extreme environments Obstacle avoidance is a largely researched field in behavior based robotics. Several methods have been the developed to avoid obstacles. The possibilities largely depend up on the amount of planning and the availability of sensors. To gain understanding about obstacle avoidance we used three different techniques namely Fuzzy logic, Potential function and dynamic window approach. We present methods for evaluating policies for obstacle avoidance behaviors. Simulation result shows our methods help robots to avoid obstacle and converge to goal location even in the situation where conventional methods failed. The importance of this work is in the increased understanding of obstacle avoidance for robot control and the applications of autonomous guided vehicle technology for industry, medicine and defense etc.