  We present SpaceAgents-1, a system for learning human and multi-robot
collaboration (HMRC) strategies under microgravity conditions. Future space
exploration requires humans to work together with robots. However, acquiring
proficient robot skills and adept collaboration under microgravity conditions
poses significant challenges within ground laboratories. To address this issue,
we develop a microgravity simulation environment and present three typical
configurations of intra-cabin robots. We propose a hierarchical heterogeneous
multi-agent collaboration architecture: guided by foundation models, a
Decision-Making Agent serves as a task planner for human-robot collaboration,
while individual Skill-Expert Agents manage the embodied control of robots.
This mechanism empowers the SpaceAgents-1 system to execute a range of
intricate long-horizon HMRC tasks.
