多机器人异步协作,快速精准发现野火
D3ARC: Time-Critical Distributed Disaster Detection for Asynchronous Cooperative Multi-Robot Systems

- 异步分布式框架,动态规划机器人探测路径
- 94%任务成功率,89.4%检测置信度,限时高效响应
- 适合应急监测、灾害救援等实时性强的场景
气候变化加剧了自然灾害的严重性和不可预测性。在野火等时间敏感的危机中,传统监测手段受限于覆盖范围、成本和人员风险,亟需自主适应的监测方案。本文提出D3ARC,一种面向异步协作多机器人系统的时序感知、高可靠野火检测分布式分层框架。该框架通过分布式感知、共享态势认知与协同行动,使多个机器人在不确定性下合作。远程控制器异步决策机器人运动,各机器人自主感知环境并决定探测位置与方式。所有操作耗时,而野火持续蔓延,因此各代理共同目标是在时限内以特定性能阈值尽快发现火灾。D3ARC集成安全导航、覆盖效率、协作与可靠性机制,并具备前瞻能力,可在执行前评估候选策略。通过真实机器人仿真、消融实验与基线对比验证,系统整体任务成功率达94%,检测置信度达89.4%。
原文摘要 · Abstract (English)
Climate change is increasing the severity and unpredictability of natural disasters. In time-critical crises such as wildfires, traditional monitoring practices remain limited by coverage, cost, and personnel risk, paving the way for autonomous and adaptive monitoring solutions. Within this context, this paper introduces D3ARC, an asynchronous distributed hierarchical framework for time-aware and reliable wildfire detection. D3ARC integrates multiple robotic agents that cooperate under uncertainty through distributed perception, shared situational awareness and coordinated actions. A remote controller asynchronously decides upon each robot's motion, while each robotic agent senses the environment and decides where and how to execute the wildfire detection. All robotic operations require time, and as time progresses, wildfires continue to spread, reducing the opportunity for early intervention. As such, all agents share a common objective: to detect a wildfire with a certain performance threshold as fast as possible and within a time limit. D3ARC integrates mechanisms for safe navigation, coverage efficiency, cooperation and reliability. It introduces a forward-looking capability that allows agents to anticipate the future by evaluating candidate strategies before execution. The framework is evaluated through realistic robotics simulations, ablation studies, and baseline comparisons, achieving an overall mission success up to 94% with 89.4% detection confidence.
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