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English(EN) CALM: Decentralized Control of Cooperative Aerial Manipulation with Multi-Agent Reinforcement Learning

新的CALM系统使用多智能体RL进行合作空中操作

研究人员开发了CALM(合作空中学习操作),这是一种新颖的去中心化控制器,专为多个无人机(UAV)协同操作共享有效载荷而设计。该系统利用多智能体强化学习(MARL),特别是多智能体近端策略优化(MAPPO),结合扩展状态观测器和预期偏航控制,以缓解风和嘈杂的目标广播等问题。与模拟中的各种基线相比,CALM在减少位置和方向误差方面表现出优越的性能。 AI

影响 这项研究可以提升无人机集群在复杂、动态环境中的能力,可能对物流和建筑业产生影响。

排序理由 该集群包含一篇学术论文,详细介绍了一种用于机器人技术中多智能体强化学习的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.MA (Multiagent) 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的CALM系统使用多智能体RL进行合作空中操作

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该集群包含一篇学术论文,详细介绍了一种用于机器人技术中多智能体强化学习的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Fausto Francesco Lizzio ·

    CALM:基于多智能体强化学习的合作空中操作的去中心化控制

    Cooperative aerial manipulation is difficult under wind, payload motion, and noisy goal broadcasts because multiple Unmanned Aerial Vehicles (UAVs) are coupled through a shared payload. We present CALM (Cooperative Aerial Learned Manipulation), a decentralized controller for aeri…