10 citations · 19 across the 9 of their papers we have counts for
9 papers · 1 filter
An Empirical Study on What Matters for Viewpoint-Generalizable Policies in Visual Imitation Learning
Mino Nakura, Sriram Krishna, Yufei Wang +3
Visual imitation learning is a promising approach to training robot manipulation policies capable of completing a wide variety of tasks. However, policies today remain brittle to v…
Force-Modulated Visual Policy for Robot-Assisted Dressing with Arm Motions
Alexis Yihong Hao, Yufei Wang, Navin Sriram Ravie +3
Robot-assisted dressing has the potential to significantly improve the lives of individuals with mobility impairments. To ensure an effective and comfortable dressing experience, t…
Geometric Red-Teaming for Robotic Manipulation
Divyam Goel, Yufei Wang, Tiancheng Wu +4
Standard evaluation protocols in robotic manipulation typically assess policy performance over curated, in-distribution test sets, offering limited insight into how systems fail un…
ArticuBot: Learning Universal Articulated Object Manipulation Policy via Large Scale Simulation
Yufei Wang, Ziyu Wang, Mino Nakura +5
This paper presents ArticuBot, in which a single learned policy enables a robotics system to open diverse categories of unseen articulated objects in the real world. This task has…
Real-World Offline Reinforcement Learning from Vision Language Model Feedback
Sreyas Venkataraman, Yufei Wang, Ziyu Wang +3
Offline reinforcement learning can enable policy learning from pre-collected, sub-optimal datasets without online interactions. This makes it ideal for real-world robots and safety…
Unfolding the Literature: A Review of Robotic Cloth Manipulation
Alberta Longhini, Yufei Wang, Irene Garcia-Camacho +9
The realm of textiles spans clothing, households, healthcare, sports, and industrial applications. The deformable nature of these objects poses unique challenges that prior work on…
RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback
Yufei Wang, Zhanyi Sun, Jesse Zhang +4
Reward engineering has long been a challenge in Reinforcement Learning (RL) research, as it often requires extensive human effort and iterative processes of trial-and-error to desi…
Force-Constrained Visual Policy: Safe Robot-Assisted Dressing via Multi-Modal Sensing
Zhanyi Sun, Yufei Wang, David Held +1
Robot-assisted dressing could profoundly enhance the quality of life of adults with physical disabilities. To achieve this, a robot can benefit from both visual and force sensing.…
RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation
Yufei Wang, Zhou Xian, Feng Chen +6
We present RoboGen, a generative robotic agent that automatically learns diverse robotic skills at scale via generative simulation. RoboGen leverages the latest advancements in fou…