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A GA-based fuzzy controller for mobile robots in dynamic environments with moving obstacles.

机译:基于GA的模糊控制器,适用于具有移动障碍物的动态环境中的移动机器人。

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摘要

In this thesis, a fuzzy-inference system with an accelerate/brake (A/B) module is developed for real-time navigation of a mobile robot. The A/B module of the proposed system provides the mobile robot with the capability of making human-like decisions as it moves toward a target. Under the control of the fuzzy inference system, the robot can perform well in avoiding both static and moving obstacles, along a reasonably short path. In addition, a genetic algorithm (GA)-based fuzzy-inference control system with an A/B module is developed for a mobile robot in complex and dynamic environments. Based on the proposed fuzzy-inference system, a GA module is designed to obtain near-optimal parameters of the membership functions, which improves the performance of the fuzzy-inference system. The GA can effectively tune the control parameters without suffering from local minima. The effectiveness of the proposed approaches are demonstrated by simulation studies. The proposed fuzzy controller is successfully implemented on a real mobile robot for wall following and obstacle avoidance.
机译:本文提出了一种带加速/制动(A / B)模块的模糊推理系统,用于移动机器人的实时导航。所提出系统的A / B模块为移动机器人提供了在朝目标移动时做出类似人的决策的能力。在模糊推理系统的控制下,机器人可以沿着合理的短路径避开静态和动态障碍物,表现出色。此外,还为复杂和动态环境中的移动机器人开发了具有A / B模块的基于遗传算法(GA)的模糊推理控制系统。在提出的模糊推理系统的基础上,设计了一种遗传算法模块,以获取隶属函数的近似最优参数,从而提高了模糊推理系统的性能。 GA可以有效地调整控制参数,而不会出现局部最小值。仿真研究证明了所提出方法的有效性。所提出的模糊控制器已成功地在真实的移动机器人上实现,用于墙面跟随和避障。

著录项

  • 作者

    Tan, Suo.;

  • 作者单位

    University of Guelph (Canada).;

  • 授予单位 University of Guelph (Canada).;
  • 学科 Engineering Robotics.;Artificial Intelligence.;Engineering System Science.
  • 学位 M.A.Sc.
  • 年度 2010
  • 页码 131 p.
  • 总页数 131
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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