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 sensorst 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. Aglobal planner, therefore, only needs to generate some subgoal positions ratherthan exact geometric paths. Because such subgoals can be easily removed from or added into the planner, this. strategy reduces computational time for globalplanning and is flekible for replanning in dynamic environments. Simulationresults demonstrate that the proposed strategy can be applied to robot motion in complex and dynamic environments. 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 sensorst 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. Aglobal planner, therefore, only needs to generate some subgoal positions ratherthan exact geometric paths. Because these subgoals can be easily removed from or added into the planner, this. strategy reduces computational time for globalplanning and is flekible for replanning in dynamic environments. Simulationresults demonstrate that the proposed strategy can be applied to robot motion in complex and dynamic environments.