单人示范教多机器人协作，效率媲美专业同步演示。
R2BC: Multi-Agent Imitation Learning from Single-Agent Demonstrations
- 人类逐个操控机器人示范，系统自动整合为团队行为
- 四组仿真任务中表现接近甚至超过同步示范的基准
- 适合真实场景下缺乏多智能体协同示范的机器人训练
模仿学习（IL）是人类教授机器人的一种自然方式，尤其在高质量示范易获取时。尽管单机器人场景中广泛应用，但将此类方法扩展至多智能体系统仍较少研究，尤其是在单个操作者需为协作机器人团队提供示范的情况下。本文提出轮转行为克隆（R2BC），使单一人类操作者可通过顺序、单智能体示范有效训练多机器人系统。该方法允许人类依次操控每个机器人，并逐步传授团队协作行为，无需在联合动作空间中进行同步示范。我们在四个多智能体仿真任务中验证，R2BC性能可达到甚至超越基于理想同步示范的基准方法。最后，我们使用真实人类示范，在两个物理机器人任务上部署了R2BC。
原文摘要 · Abstract (English)
Imitation Learning (IL) is a natural way for humans to teach robots, particularly when high-quality demonstrations are easy to obtain. While IL has been widely applied to single-robot settings, relatively few studies have addressed the extension of these methods to multi-agent systems, especially in settings where a single human must provide demonstrations to a team of collaborating robots. In this paper, we introduce and study Round-Robin Behavior Cloning (R2BC), a method that enables a single human operator to effectively train multi-robot systems through sequential, single-agent demonstrations. Our approach allows the human to teleoperate one agent at a time and incrementally teach multi-agent behavior to the entire system, without requiring demonstrations in the joint multi-agent action space. We show that R2BC methods match, and in some cases surpass, the performance of an oracle behavior cloning approach trained on privileged synchronized demonstrations across four multi-agent simulated tasks. Finally, we deploy R2BC on two physical robot tasks trained using real human demonstrations.
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