A sensor-based obstacle avoidance for a mobile robot

센서 정보를 이용한 이동 로봇의 충돌 회피

This paper proposes a sensor-based path planning method which utilizes fuzzy logic and neural network for obstacle avoidance of a mobile robot in uncertain environments. In order to acquire the information about the environment around the mobile robot, the ultrasonic sensors mounted on the front of mobile robot are used. The neural network, whose inputs are preprocessed by ultrasonic sensor readings, informs the mobile robot of the situation of environment in which mobile robot is at the present instant. Then, according to the situation class, the fuzzy rules are fired to make a decision on the mobile robot action. In addition, this method can be implemented real time since the number of fuzzy rules used to avoid the obstacle is small. Fuzzy rules are constructed based on the human reasoning and tuned by iterative simulations. The effective of the proposed avoidance method is verified by a series of simulations.