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cs.RO2026

HARP-VLA: Human-Robot Aligned Representation Learning for Vision-Language-Action Model

Xiang Zhu, Puzhen Yuan, Yichen Liu +1

Learning generalizable vision-language-action (VLA) models from large-scale human videos is promising but challenging due to cross-embodiment discrepancies in both visual observati…

cs.RO2026

Learning Generalizable Robot Policy with Human Demonstration Video as a Prompt

Xiang Zhu, Yichen Liu, Hezhong Li +1

Recent robot learning methods commonly rely on imitation learning from massive robotic dataset collected with teleoperation. When facing a new task, such methods generally require…

cs.RO2026

Dexora: Open-source VLA for High-DoF Bimanual Dexterity

Zongzheng Zhang, Jingrui Pang, Zhuo Yang +22

Vision-Language-Action (VLA) models have recently become a central direction in embodied AI, but current systems are restricted to either dual-gripper control or single-arm dextero…

cs.RO2024

Prompt a Robot to Walk with Large Language Models

Yen-Jen Wang, Bike Zhang, Jianyu Chen +1

Large language models (LLMs) pre-trained on vast internet-scale data have showcased remarkable capabilities across diverse domains. Recently, there has been escalating interest in…

cs.RO2024

Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning

Xinyang Gu, Yen-Jen Wang, Xiang Zhu +4

Humanoid robots, with their human-like skeletal structure, are especially suited for tasks in human-centric environments. However, this structure is accompanied by additional chall…

cs.RO2024

Humanoid-Gym: Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real Transfer

Xinyang Gu, Yen-Jen Wang, Jianyu Chen

Humanoid-Gym is an easy-to-use reinforcement learning (RL) framework based on Nvidia Isaac Gym, designed to train locomotion skills for humanoid robots, emphasizing zero-shot trans…