Adaptive Negotiation-rules Acquisition Methods in Decentralized AGV Transportation Systems by Reinforcement Learning with a State Space Filter

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説明

In this paper, we introduce an autonomous decentralized method for multiple Automated Guided Vehicles (AGVs). In our proposed system, each AGV as an agent computes its transportation route by referring to the static path information. route. Once potential collisions are detected, one of the two agents chosen by a negotiation rule modifies its route plan. The rules are improved by reinforcement learning with a state space filter. Then, the performance is confirmed with regard to the adaptive negotiation rules.

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詳細情報 詳細情報について

  • CRID
    1390564238097780864
  • DOI
    10.5954/icarob.2017.gs2-1
  • ISSN
    21887829
  • 本文言語コード
    en
  • データソース種別
    • JaLC
    • Crossref
    • OpenAIRE
  • 抄録ライセンスフラグ
    使用不可

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