19 citations · 35 across the 14 of their papers we have counts for
8 papers · 1 filter
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Charles Xu, Qiyang Li, Jianlan Luo +1
Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…
What Matters in Building Vision-Language-Action Models for Generalist Robots
Xinghang Li, Peiyan Li, Long Qian +10
To utilize Foundation Vision Language Models (VLMs) for robotic tasks and motion planning, the community has proposed different methods for injecting action components into VLMs an…
GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation
Chi-Lam Cheang, Guangzeng Chen, Ya Jing +9
We present GR-2, a state-of-the-art generalist robot agent for versatile and generalizable robot manipulation. GR-2 is first pre-trained on a vast number of Internet videos to capt…
World Model-based Perception for Visual Legged Locomotion
Hang Lai, Jiahang Cao, Jiafeng Xu +5
Legged locomotion over various terrains is challenging and requires precise perception of the robot and its surroundings from both proprioception and vision. However, learning dire…
GR-MG: Leveraging Partially Annotated Data via Multi-Modal Goal-Conditioned Policy
Peiyan Li, Hongtao Wu, Yan Huang +3
The robotics community has consistently aimed to achieve generalizable robot manipulation with flexible natural language instructions. One primary challenge is that obtaining robot…
IRASim: A Fine-Grained World Model for Robot Manipulation
Fangqi Zhu, Hongtao Wu, Song Guo +3
World models allow autonomous agents to plan and explore by predicting the visual outcomes of different actions. However, for robot manipulation, it is challenging to accurately mo…
SInViG: A Self-Evolving Interactive Visual Agent for Human-Robot Interaction
Jie Xu, Hanbo Zhang, Xinghang Li +3
Linguistic ambiguity is ubiquitous in our daily lives. Previous works adopted interaction between robots and humans for language disambiguation. Nevertheless, when interactive robo…
Towards Unified Interactive Visual Grounding in The Wild
Jie Xu, Hanbo Zhang, Qingyi Si +3
Interactive visual grounding in Human-Robot Interaction (HRI) is challenging yet practical due to the inevitable ambiguity in natural languages. It requires robots to disambiguate…