Fuzzy logic based robot navigation in uncertain environments

This paper presents a strategy for fuzzy logic based robot navigation in uncertain environments by multisensor integration. The main idea of the study is to coordinate conflicts and competitions among multiple reactive behaviors efficiently by fuzzy sets and a rule base. To achieve this objective, an array of ultrasonic sensors and a vision system are mounted on a mobile robot. The ultrasonic sensors provide distance information between the robot

and obstacles for behavior control of the mobile robot, while the vision system identifies some subgoals for determining a good motion direction to avoid robot trap in local region. The simulation results show that the proposed strategy, by integrating ultrasonic sensors and the vision system, can be efficiently applied to robot navigation in complex and uncertain environments by using different behaviors, such as avoiding obstacles, decelerating at curved and narrow roads, escaping from a U-shaped object, and moving to target and so on. I. Intrduction If a mobile robot moves in unknown environments to reach a specified target without collisions with obstacles, sensors must be used to acquire information about the real world. Using such information, it is very difficult to build a precise world model in real-time for preplanning a collision-free path. On the basis of situationally reactive behaviors, behavior based control [1][2][3] has been proposed for robot navigation. Since this method does not need building an entire world model and complex reasoning process, it is suitable for robot control in dynamic environments. A key issue in behavior based control is how to coordinate conflicts and competitions among multiple reactive behaviors efficiently. The example in Fig.1 shows that the robot must efficiently weight multiple reactive behaviors, such as avoiding obstacle, following edge, and moving to target and so on., according to range information, when it reaches a target inside a U-shaped object. The usual approach for implementing behavior control is artificial potential fields [4][5][6]. A drawback to this approach is that during preprogramming much effort must be made to test and to adjust some thresholds regarding potential fields for avoiding obstacle, wandering, and moving to target and so on. In particular, these thresholds frequently depend on environments. Fig. 1 : Robot motion to reach a target In [7][8], we present an approach for fuzzy logic based behavior control of a mobile robot. Unlike behavior control based on artificial potential fields, this method is to compute weights of multiple reactive behaviors in dynamic environments by a fuzzy logic algorithm rather than simply to inhibit some reactive behaviors with lower levels. In this paper, we further present a strategy for fuzzy logic based behavior control of a mobile robot by multisensor integration. To achieve this objective, an array of ultrasonic sensors and a vision system are mounted on a mobile robot. The ultrasonic sensors provide distance information between the robot and...

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