6 papers · 1 filter
DexVLA: Vision-Language Model with Plug-In Diffusion Expert for General Robot Control
Junjie Wen, Yichen Zhu, Jinming Li +3
Enabling robots to perform diverse tasks across varied environments is a central challenge in robot learning. While vision-language-action (VLA) models have shown promise for gener…
Diffusion-VLA: Generalizable and Interpretable Robot Foundation Model via Self-Generated Reasoning
Junjie Wen, Minjie Zhu, Yichen Zhu +8
In this paper, we present DiffusionVLA, a novel framework that seamlessly combines the autoregression model with the diffusion model for learning visuomotor policy. Central to our…
ChatVLA-2: Vision-Language-Action Model with Open-World Embodied Reasoning from Pretrained Knowledge
Zhongyi Zhou, Yichen Zhu, Junjie Wen +2
Vision-language-action (VLA) models have emerged as the next generation of models in robotics. However, despite leveraging powerful pre-trained Vision-Language Models (VLMs), exist…
WorldEval: World Model as Real-World Robot Policies Evaluator
Yaxuan Li, Yichen Zhu, Junjie Wen +2
The field of robotics has made significant strides toward developing generalist robot manipulation policies. However, evaluating these policies in real-world scenarios remains time…
ObjectVLA: End-to-End Open-World Object Manipulation Without Demonstration
Minjie Zhu, Yichen Zhu, Jinming Li +6
Imitation learning has proven to be highly effective in teaching robots dexterous manipulation skills. However, it typically relies on large amounts of human demonstration data, wh…
ChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action Model
Zhongyi Zhou, Yichen Zhu, Minjie Zhu +8
Humans possess a unified cognitive ability to perceive, comprehend, and interact with the physical world. Why can't large language models replicate this holistic understanding? Thr…