Scalable Multi-Human Cooperative Manipulation via Commander-Executor Coordination

This research proposes a hierarchical commander-executor framework for multi-human cooperative object manipulation. The commander generates semantic and geometric plans, while the executor learns physics-based policies for coordinated interactions. The method is evaluated on various tasks, showing improved success rates over state-of-the-art approaches and scalability to multi-agent settings.