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基于模糊神经网络的移动机器人轨迹实时跟踪

Real-Time Trajectory Tracking of Wheel Mobile Robot Based on Fuzzy Neural Networks

中文摘要英文摘要

论文主要研究无障碍环境下轮式移动机器人的轨迹实时跟踪运动控制问题。通过对目前主要采用的几种轨迹跟踪控制方法分析,论文基于模糊逻辑推理思想和神经网络学习功能,构造了一种模糊神经网络控制器,实现对轮式移动机器人的轨迹跟踪控制。同时通过对神经网络结构的有效设计和参数学习算法研究,实现了轨迹的实时跟踪。计算机仿真的效果与目前研究的几种方法比较,显示了本文设计方法的有效性和优越性。最后论文基于加拿大DrRobot公司的WiRobotX80机器人实验平台,完成了移动机器人实时轨迹跟踪的模拟试验.为分析本文设计的控制器的性能,比较了计算机仿真实验和模拟实验的结果,得到的结果为轮式移动机器人的设计和控制提供了有用的参考。

he subject of this paper is the motion control problem of wheeled mobile robots (WMRs) in environments without obstacles. After Analyzing and comparing main trajectory tracking control ways used at present, a fuzzy neural network controller is presented to realize the wheel mobile robot’s trajectory tracking and motion control based on the idea of fuzzy logic reasoning and neural network learning function. With reference to the structure and parameter learning way of fuzzy neural network controller, they are improved to lead to a solution of real-time trajectory tracking. The computer simulation resaults, which are compared its performance with that of several existing control ways in a number of computer simulation experiments, show that the fuzzy neural network control is effective and superiority. The implementation of this approach on the WiRobotX80 which is made by DrRobot Company in Canada is finished. WiRobotX80 is a three-wheel mobile robot, which is described in detail in paper. To assess the quality of the proposed controller, we compare the simulation result and WiRobotX80 WMR experiment result. The obtained results provide useful guidelines for WMR control designers.

田献军、刘清、郭建明

自动化技术、自动化技术设备计算技术、计算机技术自动化基础理论

轮式移动机器人模糊神经网络轨迹实时跟踪

Wheel Mobile RobotFuzzy Neural NetworksReal-Time Trajectory Tracking

田献军,刘清,郭建明.基于模糊神经网络的移动机器人轨迹实时跟踪[EB/OL].(2008-10-10)[2025-08-18].http://www.paper.edu.cn/releasepaper/content/200810-190.点此复制

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