Publikation
Multi-Embodiment Locomotion at Scale with extreme Embodiment Randomization
Nico Bohlinger; Jan Peters
In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2509.02815, Pages 1-5, arXiv, 2025.
Zusammenfassung
We present a single, general locomotion policy
trained on a diverse collection of 50 legged robots. By combining
an improved embodiment-aware architecture (URMAv2) with
a performance-based curriculum for extreme Embodiment
Randomization, our policy learns to control millions of mor-
phological variations. Our policy achieves zero-shot transfer to
unseen real-world humanoid and quadruped robots.