未知环境下机器人导航的新型平均神经模糊混合控制技术研究

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引用次数: 0

摘要

目前的研究重点是开发和分析用于高度混乱环境下移动机器人路径规划和导航的新型平均神经模糊控制器。在调查过程中,分析了与机器人、控制和导航相关的各种研究。为了绘制环境地图,机器人上安装了几个距离传感器。传感器对环境的读数被分成不同的扇区(前、左、右和后扇区)。在从起点到目标点的导航过程中,使用传感器读取机器人与环境中存在的障碍物进行协商。在目前的研究中,从各种练习中得到的实验和模拟结果是一致的,误差在3%以内。结果表明,该方法在复杂环境下的机器人导航中是有效的。该技术可用于解决各种工程优化问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Novel Average Neuro Fuzzy Hybrid Control Technique for Robot Navigation in Unknown Environments
The current research focuses on development and analysis of novel Average Neuro-Fuzzy Controller for path planning and navigation of mobile robot in highly cluttered environment. During the investigation various researches related to robot, control and navigation have been analysed. For mapping the environments several distance sensors mounted on the robot are used. The sensors readings about the environments have been segmented into various sectors (front, left, right and back sectors). Using the sensors reading robots negotiate with the obstacles present in the environments during navigation from start to goal point. Experimental and simulation results obtained during the current research from various exercises are in agreement and are within 3%. Comparisons between results show the effectiveness of the proposed technique for robot navigation in complex environments. This technique can be used to address various engineering optimisation problems.
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