Kazan (Volga region) Federal University, KFU
KAZAN
FEDERAL UNIVERSITY
 
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TRANSFER OF LEARNED EXPLORATION STRATEGIES OF A MOBILE ROBOT FROM A SIMULATED TO REAL ENVIRONMENTS
Form of presentationArticles in international journals and collections
Year of publication2019
Языканглийский
  • Magid Evgeniy Arkadevich, author
  • Sagitov Artur Gazizovich, author
  • Sagitov Artur Gazizovich, postgraduate kfu
  • Sagitov Artur Gazizovich, postgraduate kfu
  • Bibliographic description in the original language Sagitov Artur, Takano Tetsuto, Muto Shohei, Magid Evgeni. Transfer of learned exploration strategies of a mobile robot from a simulated to real environments//ICAROB 2019: PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS. - 2019. - Vol., Is.. - P.120-123.
    Annotation Reinforcement learning based approaches show promises in various robotic applications, but a significant amount of time and resources are required for a robot to learn optimal behavior. Using virtual environments, we could significantly speed up and improve performance of a target task. We implemented a reinforcement learning based exploration algorithm for a mobile robot, training in Gazebo environment and transferring learned strategy to a real robot. We show that it is convenient and appropriate to use simulation to train strategies for mobile robots.
    Keywords navigation; algorithm; mobile robots; reinforcement learning; exploration
    The name of the journal ICAROB 2019: PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS
    Please use this ID to quote from or refer to the card https://repository.kpfu.ru/eng/?p_id=196702&p_lang=2
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