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AIT-Rescue is the champion team in the RoboCup 2024 Rescue Simulation League that succeeded in proposing a rescue strategy focused on distributed control. RoboCupRescue Simulation is a competition that aims to develop rescue strategies to save more civilians in disaster rescue simulations. AIT-Rescue employs autonomous distributed decision-making and has a flexible rescue strategy that can be adopted for complex disaster situations. This paper explains the rescue strategy of AIT-Rescue and the implemented module design. The critical features in this system are the methods for determining priority roads and selecting sanctuaries. The processes that these methods consider for civilian rescue in disaster conditions are explained. The research results on multiagent systems are presented in relation to AIT-Rescue’s development. This research contributes to developing effective strategies for real-world disaster rescue by exploring multiagent systems and applying them to complex disaster scenarios. In the future, these results will be integrated into agents to obtain better strategies.

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Designing a Rescue Strategy Emphasizing Distributed Control in RoboCupRescue Simulation

  • 会议论文

  • 发表日期：

    2025年

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  • Keisuke Ando,
  • Ryoya Maeda,
  • Haruki Uehara,
  • Joe Fujisawa,
  • Itsuki Matsunaga,
  • Ryosuke Suzuki,
  • Kota Kato,
  • Yuki Shimada,
  • Shuntarou Fujii,
  • Takeshi Uchitane,
  • Kazunori Iwata,
  • Nobuhiro Ito

摘要

AIT-Rescue is the champion team in the RoboCup 2024 Rescue Simulation League that succeeded in proposing a rescue strategy focused on distributed control. RoboCupRescue Simulation is a competition that aims to develop rescue strategies to save more civilians in disaster rescue simulations. AIT-Rescue employs autonomous distributed decision-making and has a flexible rescue strategy that can be adopted for complex disaster situations. This paper explains the rescue strategy of AIT-Rescue and the implemented module design. The critical features in this system are the methods for determining priority roads and selecting sanctuaries. The processes that these methods consider for civilian rescue in disaster conditions are explained. The research results on multiagent systems are presented in relation to AIT-Rescue’s development. This research contributes to developing effective strategies for real-world disaster rescue by exploring multiagent systems and applying them to complex disaster scenarios. In the future, these results will be integrated into agents to obtain better strategies.