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Physics-informed multi-agent reinforcement learning with multi-scale graph perception for multi-robot coordination
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DOI：10.1016/j.eswa.2026.133930.png)
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摘要
En 中文
• 物理引导控制提高了大型机器人团队的协调性。• 长距离团队感知与稳定的局部决策相结合。• 该方法提高了导航和空间采样性能。• 在噪声链路和机器人故障下仍能保持鲁棒性能。• 该方法可扩展至更大的机器人团队，无需额外训练。
Keyword:
Multi-robot systems
Multi-agent reinforcement learning
Physics-informed control
Port-Hamiltonian systems
Graph neural networks
Long-range coordination
期刊
IF:
7.5
论文数:
3.0W
被引数:
10.2W
机构
暂无机构信息
引用论文
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