Autonomous grading work using deep reinforcement learning based control

Masayuki Nakatani, Zeyuan Sun, Yutaka Uchimura

研究成果: Conference contribution

抜粋

The field of artificial intelligence (AI) has advanced significantly over the years. One of its achievements is the deep reinforcement learning algorithm using which AI can play some Atari 2600 games better than humans. In this paper, optimal route of construction machines such as bulldozers is modeled based on deep reinforcement learning. The aim of this study is to apply deep reinforcement learning to a grading machine to enable it to grade various surface types autonomously. A simple grading simulator is created to simulate the grading task. In addition, the overall scenario is made visible to the network by entering the simulation into the network so that human operators can construct suitable ground path from the surrounding sediment environment. The method is evaluated with the grading simulator, and the agent is shown to exhibit desirable control behavior and fulfill the goals of the simple grading simulation. Despite the environment being virtual, the simulation results demonstrate the feasibility of the proposed approach.

元の言語English
ホスト出版物のタイトルProceedings
ホスト出版物のサブタイトルIECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
出版者Institute of Electrical and Electronics Engineers Inc.
ページ5068-5073
ページ数6
ISBN(電子版)9781509066841
DOI
出版物ステータスPublished - 2018 12 26
イベント44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 - Washington, United States
継続期間: 2018 10 202018 10 23

出版物シリーズ

名前Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

Conference

Conference44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018
United States
Washington
期間18/10/2018/10/23

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Control and Optimization

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  • これを引用

    Nakatani, M., Sun, Z., & Uchimura, Y. (2018). Autonomous grading work using deep reinforcement learning based control. : Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society (pp. 5068-5073). [8591189] (Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECON.2018.8591189