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A fuzzy logic information fusion algorithm for autonomous mobile robot avoidance based on multi-ultrasonic range sensors

机译:基于多超声波测距传感器的自动移动机器人规避模糊逻辑信息融合算法

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Obstacle-avoiding is a key and challenging issue for autonomous mobile robot navigation, especially in unstructured environments. This paper proposes a fuzzy logic information fusion algorithm based on multi-ultrasonic ranging sensors. Compared to the single sensor approach, this algorithm can not only get the obstacle's distance and orientation information more accurately and reliably, but also obtain the numerical output results of the speed and the turning angle for robot's obstacle avoiding behavior. In addition, the method can simplify the system design by eliminating the necessity of temperature compensation which is routinely included in ultrasonic ranging. MATLAB based simulations and the local path finding experiments on the prototype autonomous mobile robot showed that this algorithm can help the robot timely and robustly to avoid the obstacles in an unstructured environment in a more correct and reliable way, in the same time, the guided path is more smooth and the fluctuation is less and more reasonable. Obviously, the algorithm proposed in the paper is effective.
机译:避免障碍是自主移动机器人导航的一个关键且具有挑战性的问题,尤其是在非结构化环境中。提出了一种基于多超声测距传感器的模糊逻辑信息融合算法。与单传感器方法相比,该算法不仅可以更准确,更可靠地获得障碍物的距离和方向信息,而且可以获得机器人避障行为的速度和转角的数值输出结果。另外,该方法可以消除通常包括在超声波测距中的温度补偿的必要性,从而简化系统设计。基于MATLAB的仿真和原型自主移动机器人的局部路径发现实验表明,该算法可以以更正确,更可靠的方式,帮助机器人及时,稳健地避免在非结构化环境中遇到的障碍,同时引导路径更平滑,波动越来越小。显然,本文提出的算法是有效的。

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