arXiv:2503.20723cs.ROcs.MA2025-03

解决机器人协同中的执行器限制问题,实现节能高效会合

Multi-Robot Coordination Under Physical Limitations

  • 基于庞特里亚金极小值原理设计约束优化控制策略
  • 在轮速饱和条件下仍保持稳定高效会合,能耗显著降低
  • 适用于真实场景中的多机器人协同,抗通信延迟与噪声

多机器人协同在自主探索、搜救和协同运输等应用中至关重要。本文提出一种最优一致性框架,用于多机器人系统(MRS)的高效会合,同时最小化能耗并处理执行器约束。现实部署中的关键挑战是执行器限制,尤其是轮速饱和,会严重影响控制性能。为此,将庞特里亚金极小值原理(PMP)融入控制设计,实现带约束的优化,确保系统稳定性和可行性。所提最优控制策略在存在执行约束时仍能有效平衡协同效率与能耗。通过大量数值仿真及使用Robotarium移动机器人团队的真实实验验证,结果表明该控制方法在应对通信延迟、传感器噪声和数据包丢失等实际挑战下,可实现可靠且高效的协同会合。

原文摘要 · Abstract (English)

Multi-robot coordination is fundamental to various applications, including autonomous exploration, search and rescue, and cooperative transportation. This paper presents an optimal consensus framework for multi-robot systems (MRSs) that ensures efficient rendezvous while minimizing energy consumption and addressing actuator constraints. A critical challenge in real-world deployments is actuator limitations, particularly wheel velocity saturation, which can significantly degrade control performance. To address this issue, we incorporate Pontryagin Minimum Principle (PMP) into the control design, facilitating constrained optimization while ensuring system stability and feasibility. The resulting optimal control policy effectively balances coordination efficiency and energy consumption, even in the presence of actuation constraints. The proposed framework is validated through extensive numerical simulations and real-world experiments conducted using a team of Robotarium mobile robots. The experimental results confirm that our control strategies achieve reliable and efficient coordinated rendezvous while addressing real-world challenges such as communication delays, sensor noise, and packet loss.

多机器人协同控制最优控制

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