Topology Acquisition in Unknown Environment and Learn the Route to Destination Point by Autonomous Mobile Robots

DOI Web Site Web Site 5 References
  • Iwasa Mutsumi
    Graduate School of System Design, Tokyo Metropolitan University
  • Toda Yuichiro
    Graduate School of Natural Science and Technology, Okayama University
  • Arai Tomoyuki
    Graduate School of System Design, Tokyo Metropolitan University
  • Kubota Naoyuki
    Graduate School of System Design, Tokyo Metropolitan University

Bibliographic Information

Other Title
  • 自律移動ロボットによる未知環境の位相構造獲得と目標物への経路学習
  • ジリツ イドウ ロボット ニ ヨル ミチ カンキョウ ノ イソウ コウゾウ カクトク ト モクヒョウブツ エ ノ ケイロ ガクシュウ

Search this article

Description

<p>It is an important task for mobile robots that search the target and learn the route while recognizing the unknown environment topology. Usually, reinforcement learning is used as a learning method to know the route to the target while exploring the environment. However, in an unknown environment, it is difficult to predict the number of state division. Particularly, when the state division is too fine, the amount of calculation increases exponentially. In this paper, we propose a method to dynamically construct the state space of the environment using Growing Neural Gas and simultaneously search and learn the route to the target using Q-Learning. We applied multiple autonomous mobile robots to increase searching efficiency. The experimental result shows the effectiveness of the proposed method that can respond to dynamic environmental change.</p>

Journal

References(5)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top