arXiv:2605.08020
Active Embodiment Identification with Reinforcement Learning for Legged Robots
Active Embodiment Identification with Reinforcement Learning for Legged Robots
著者: Nico Bohlinger, Jan Peters
分類: cs.RO
原文アブストラクト
We present an active embodiment identification method for legged robots that jointly learns information-seeking behavior and explicit embodiment prediction. Using a history-augmented URMA architecture, the method infers joint-level and global embodiment parameters through interaction with the environment in simulation across different morphologies.