추론 이론과 퍼지 컨트롤러 결합에 의한 이동 로봇의 자유로운 주변 환경 인식

Reliable Navigation of a Mobile Robot in Cluttered Environment by Combining Evidential Theory and Fuzzy Controller

This paper develops a sensor based navigation method that utilizes fuzzy logic and the Dempster-Shafer evidence theory for mobile robot in uncertain environment. The proposed navigator consists of two behaviors: obstacle avoidance and goal seeking. To navigate reliably in the environment, we make a map building process before the robot finds a goal position and create a robust fuzzy controller. In this paper, the map is constructed on a two-dimensional occupancy grid. The sensor readings are fused into the map using D-S inference rule. Whenever the robot moves, it catches new information about the environment and replaces the old map with new one. With that process the robot can go wandering and finding the goal position. The usefulness of the proposed method is verified by a series of simulations. This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper.