Fuzzy logic based behavior fusion for navigation of an intelligent mobile robot

This paper presents a new method for behavior fusion control of a mobile robot in uncertain environments. Using behavior fusion by fuzzy logic, a mobile robot is able to directly execute its motion according to range information about environments, acquired by ultrasonic sensors, without the need for trajectory planning. Based on low-level behavior control, an efficient strategy for integrating high-level global planning for robot motion can be formulated, since, in most applications, some information on environments is prior knowledge. A global planner, therefore, only needs to generate some subgoal positions rather than exact geometric paths. Because such subgoals can be easily removed from or added into the planner, this strategy reduces computational time for global planning and is flexible for replanning in dynamic environments. Simulation results demonstrate that the proposed strategy can be applied to robot motion in complex and dynamic environments.