# MARL-Exo: Multi-Agent Reinforcement Learning Co-Adapts Hip Exoskeleton Control to Reduce Metabolic Energy Cost

- Source: arXiv cs.RO
- Published: 2026-10-28T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/sjjgekf0vqx03b8yw4vs90tz5
- Original: https://arxiv.org/abs/2610.37441

## Summary

The study proposes MARL-Exo, a multi-agent reinforcement learning framework in which a full-body musculoskeletal model and a bilateral hip exoskeleton policy are co-trained in simulation in two stages; the exoskeleton observes only delayed hip kinematics and past commands. In simulation, the metabolic policy reduced modeled muscle metabolic power by 13.8% compared with walking without the device, and by 8.8% after adding mechanical-power shaping.