43 citations · 54 across the 7 of their papers we have counts for
7 papers
Demonstration Synthesis from a Single Scan via Gaussian Splatting for Visuomotor Policy Learning
Beichen Wang, Yuen-Hei Yeung, V. R. Sridhar Devarakonda +1
Training a visuomotor policy calls for abundant demonstrations that closely match the target environment, yet collecting them anew remains expensive. Existing demonstration synthes…
Learning Scene-Aware Humanoid Locomotion through 3D Clutter from Immersive Human Demonstrations
Beichen Wang, Tong Xu, Daniel Kosukhin +3
While learning from human motions has enabled highly dynamic humanoid skills such as dancing and martial arts in obstacle-free space, traversal through densely cluttered environmen…
RoamFlow: Reinforcement-Aligned One-Step Action MeanFlow Policy for Image-Goal Navigation
Zixuan Zhang, Yuqi Chen, Junjie Gao +4
Image-goal navigation is a key challenge in embodied robotics, where an agent must reach a target specified solely by a goal image. While existing reinforcement learning approaches…
Moving Through Clutter: Scaling Data Collection and Benchmarking for 3D Scene-Aware Humanoid Locomotion via Virtual Reality
Beichen Wang, Yuanjie Lu, Linji Wang +2
Recent advances in humanoid locomotion have enabled dynamic behaviors such as dancing, martial arts, and parkour, yet these capabilities are predominantly demonstrated in open, fla…
APPLV: Adaptive Planner Parameter Learning from Vision-Language-Action Model
Yuanjie Lu, Beichen Wang, Zhengqi Wu +4
Autonomous navigation in highly constrained environments remains challenging for mobile robots. Classical navigation approaches offer safety assurances but require environment-spec…
When language and vision meet road safety: leveraging multimodal large language models for video-based traffic accident analysis
Ruixuan Zhang, Beichen Wang, Juexiao Zhang +3
The increasing availability of traffic videos functioning on a 24/7/365 time scale has the great potential of increasing the spatio-temporal coverage of traffic accidents, which wi…
VLM See, Robot Do: Human Demo Video to Robot Action Plan via Vision Language Model
Beichen Wang, Juexiao Zhang, Shuwen Dong +2
Vision Language Models (VLMs) have recently been adopted in robotics for their capability in common sense reasoning and generalizability. Existing work has applied VLMs to generate…