Human Perception Based Obstacle Avoidance and Path Planning of Wheeled Mobile Robot

This paper presents a Rule Based Fuzzy Logic approach for automatic reaction control of mobile robots in an uncertain environment. The fuzzy rules anticipated for escaping the obstacles are derived from the experience of human responses to the environment that guides the robot for shortest path to reach the goal. Heuristic rules governing the robot are appropriately created according to various situations illustrated by the obstacle locations, the target orientation and the robot direction of movement. The target plays a significant role in deciding the rotating angle of the robot when the obstacles are close. Sensed information of obstacle position and comparative target location are inputs for the robot, while the steering angle is the output to drive the mobile robot. The competency of the approach proposed is verified by means of the simulation results, where a robot moves in a variety of environments with obstacles of different shapes and sizes.