A Sensor-Based Navigation Algorithm for a Mobile robot using Fuzzy Logic

Int. J. Robotics Autom. Pub Date : 2006-04-01 DOI:10.2316/Journal.206.2006.2.206-2797

Xiaoyu Yang, M. Moallem, Rajnikant V. Patel

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引用次数: 5

Abstract

In this paper, the "goal-unreachable" problems found in fuzzy logic-based algorithms for mobile robot navigation systems are studied. Two algorithms based on sensory information are developed to address problems with Goal-Unreachable with Large Obstacles (GUWLO) and Goal-Unreachable with Nearby Obstacles (GUWNO). The GUWLO problem occurs when the absolute value of the target angle is large and the directions to the left (or right) are completely blocked. This is alleviated by interpolating a temporary target angle considering the surface feature of the obstacle in front of the robot. The GUWNO problem arises because of the repulsive influence from obstacles close to the goal position. It is overcome by including an eliminator e in the fuzzy navigation system, taking into account the relative distance between the robot and its goal position. The resulting navigation system is implemented on a real mobile robot, Koala, and tested in various environments. Experimental results are presented that demonstrate the effectiveness of the resulting fuzzy navigation system and its improved performance over conventional fuzzy logic navigation algorithms.

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基于模糊逻辑的移动机器人传感器导航算法

研究了基于模糊逻辑的移动机器人导航算法中存在的“目标不可达”问题。针对大障碍物目标不可达(GUWLO)和近障碍物目标不可达(GUWNO)问题，提出了两种基于感官信息的算法。当目标角度绝对值较大且向左(或向右)方向完全被遮挡时，就会出现GUWLO问题。考虑到机器人前方障碍物的表面特征，通过插值一个临时目标角度来缓解这一问题。GUWNO问题是由于靠近目标位置的障碍物的排斥影响而产生的。通过在模糊导航系统中加入消除器e，考虑到机器人与其目标位置之间的相对距离，克服了这一问题。由此产生的导航系统在一个真正的移动机器人Koala上实现，并在各种环境中进行了测试。实验结果表明，所得到的模糊导航系统是有效的，其性能优于传统的模糊逻辑导航算法。

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Int. J. Robotics Autom.

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