4 papers
It Takes Two: Learning Interactive Whole-Body Control Between Humanoid Robots
Zuhong Liu, Junhao Ge, Minhao Xiong +4
The true promise of humanoid robotics lies beyond single-agent autonomy: two or more humanoids must engage in physically grounded, socially meaningful whole-body interactions that…
RoCo-Sim: Enhancing Roadside Collaborative Perception through Foreground Simulation
Yuwen Du, Anning Hu, Zichen Chao +6
Roadside Collaborative Perception refers to a system where multiple roadside units collaborate to pool their perceptual data, assisting vehicles in enhancing their environmental aw…
Towards Collaborative Autonomous Driving: Simulation Platform and End-to-End System
Genjia Liu, Yue Hu, Chenxin Xu +8
Vehicle-to-everything-aided autonomous driving (V2X-AD) has a huge potential to provide a safer driving solution. Despite extensive researches in transportation and communication t…
Unraveling the Effects of Synthetic Data on End-to-End Autonomous Driving
Junhao Ge, Zuhong Liu, Longteng Fan +5
End-to-end (E2E) autonomous driving (AD) models require diverse, high-quality data to perform well across various driving scenarios. However, collecting large-scale real-world data…