Navigation control of mobile robot using interval type-2 neural fuzzy controller optimized by dynamic group differential evolution

Tzu Chao Lin, Chao-Chun Chen, Cheng Jian Lin

研究成果: Article

2 引文 (Scopus)

摘要

This study developed and effectively implemented an efficient navigation control of a mobile robot in unknown environments. The proposed navigation control method consists of mode manager, wall-following mode, and towards-goal mode. The interval type-2 neural fuzzy controller optimized by the dynamic group differential evolution is exploited for reinforcement learning to develop an adaptive wall-following controller. The wall-following performance of the robot is evaluated by a proposed fitness function. The mode manager switches to the proper mode according to the relation between the mobile robot and the environment, and an escape mechanism is added to prevent the robot falling into the dead cycle. The experimental results of wall-following show that dynamic group differential evolution is superior to other methods. In addition, the navigation control results further show that the moving track of proposed model is better than other methods and it successfully completes the navigation control in unknown environments.

原文English
期刊Advances in Mechanical Engineering
10
發行號1
DOIs
出版狀態Published - 2018 一月 1

指紋

Mobile robots
Navigation
Controllers
Managers
Robots
Reinforcement learning
Switches

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering

引用此文

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