VLA전문가샘플 브리프
π0.5: a Vision-Language-Action Model with Open-World Generalization
Co-training a VLA on heterogeneous data (multi-robot, web, high-level subtask labels) lets a mobile manipulator clean unseen homes end-to-end.
새로 나온 로봇, 피지컬 AI 논문과, 각 논문이 업계에 갖는 의미.
Co-training a VLA on heterogeneous data (multi-robot, web, high-level subtask labels) lets a mobile manipulator clean unseen homes end-to-end.
A slow VLM planner (7–9 Hz) and a fast visuomotor policy (200 Hz) control a full humanoid upper body from language.
RL policies trained in GPU simulation transfer zero-shot to a commodity humanoid on rough terrain.
Survey of sensor modalities, coverage and learning methods for in-hand manipulation.
A video world model trained on robot egocentric footage predicts outcomes of actions for evaluation and planning.
Cobot adoption in Korean SMEs is limited by integration cost more than by unit price.
논문은 arXiv 로봇 피드에서 가져옵니다. 요약이 아직 작성되지 않은 논문은 초록의 첫 부분을 보여줍니다.