EgoAlign: Bridging the Human-Humanoid Gap for Long-Range Loco-Manipulation
아직 한국어판이 없어 영어 원문으로 표시.
초록 발췌
Egocentric human demonstrations offer an accessible source of task experience, but differences in body scale and controller response, together with missing robot states, limit their value as humanoid training supervision. We present EgoAlign, a data-construction framework that converts these demonstrations into action and state supervision compatible with a general-purpose, continuous whole-body controller, without collecting physical-robot demonstrations.
초록에서 가져왔습니다. 요약을 준비 중입니다.