A practical fuzzy controller with Q-learning approach for the path tracking of a walking-Aid robot

Chun Tse Lin, Hsin Han Chiang, Tsu Tian Lee

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)

Abstract

This study tackles the path tracking problem of a prototype walking-Aid (WAid) robot which features the human-robot interactive navigation. A practical fuzzy controller is proposed for the path tracking control under reinforcement learning ability. The inputs to the designed fuzzy controller are the error distance and the error angle between the current and the desired position and orientation, respectively. The controller outputs are the voltages applied to the left- And right-wheel motors. A heuristic fuzzy control with the Sugeno-type rules is then designed based on a model-free approach. The consequent part of each fuzzy control rule is designed with the aid of Q-learning approach. The design approach of the controller is presented in detail, and effectiveness of the controller is demonstrated by hardware implementation and experimental results under human-robot interaction environment. The results also show that the proposed path tracking control methods can be easily applied in various wheeled mobile robots.

Original languageEnglish
Pages888-893
Number of pages6
Publication statusPublished - 2013
Externally publishedYes
Event2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013 - Nagoya, Japan
Duration: 2013 Sep 142013 Sep 17

Conference

Conference2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013
Country/TerritoryJapan
CityNagoya
Period2013/09/142013/09/17

Keywords

  • Fuzzy controller
  • Fuzzy q-learning
  • Path-tracking
  • Walking-Aid robots

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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