A reinforcement-learning approach to robot navigation

Mu Chun Su, De Yuan Huang, Chien Hsing Chou, Chen Chiung Hsieh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

This paper presents a reinforcement-learning approach to a navigation system which allows a goal-directed mobile robot to incrementally adapt to an unknown environment. Fuzzy rules which map current sensory inputs to appropriate actions are built through the reinforcement learning. Simulation results illustrate the performance of the proposed navigation system.

Original languageEnglish
Title of host publicationConference Proceedings - 2004 IEEE International Conference on Networking, Sensing and Control
Pages665-669
Number of pages5
StatePublished - 2004
EventConference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control - Taipei, Taiwan
Duration: 21 Mar 200423 Mar 2004

Publication series

NameConference Proceeding - IEEE International Conference on Networking, Sensing and Control
Volume1

Conference

ConferenceConference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control
Country/TerritoryTaiwan
CityTaipei
Period21/03/0423/03/04

Keywords

  • Navigation
  • Neural network
  • Neuro-fuzzy system
  • Reinforcement learning
  • Robot

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