1 citations · 1 across the 7 of their papers we have counts for
7 papers
Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Driving
Zongzheng Zhang, Jijun Wang, Saining Zhang +8
Traffic elements such as traffic lights and road signs play a fundamental role in human driving decisions and should naturally influence end-to-end driving performance. However, ex…
muSync-GS: Physics-Synchronized Driving Video Synthesis for Weather and Geometric Road Hazards
Yang Chen, Yicheng Zhu, Tao Li +1
High-quality driving data are essential for autonomous-driving systems and generative world models. However, rare and safety-critical scenarios involving adverse weather, braking u…
SceneFactory: GPU-Accelerated Multi-Agent Driving Simulation with Physics-Based Vehicle Dynamics
Yicheng Zhu, Yang Chen, Tao Li +1
Autonomous-driving simulators typically trade physical fidelity for scalable parallelism. Physics-based platforms such as CARLA and MetaDrive provide articulated vehicle dynamics a…
Do Open-Loop Metrics Predict Closed-Loop Driving? A Cross-Benchmark Correlation Study of NAVSIM and Bench2Drive
Yiru Wang, Anqing Jiang, Shuo Wang +4
Open-loop evaluation offers fast, reproducible assessment of autonomous driving planners, but its ability to predict real closed-loop driving performance remains questionable. Prio…
Dexbotic: Open-Source Vision-Language-Action Toolbox
Bin Xie, Erjin Zhou, Fan Jia +36
In this paper, we present Dexbotic, an open-source Vision-Language-Action (VLA) model toolbox based on PyTorch. It aims to provide a one-stop VLA research service for professionals…
Never Too Rigid to Reach: Adaptive Virtual Model Control with LLM- and Lyapunov-Based Reinforcement Learning
Jingzehua Xu, Yangyang Li, Yangfei Chen +2
Robotic arms are increasingly deployed in uncertain environments, yet conventional control pipelines often become rigid and brittle when exposed to perturbations or incomplete info…
RoboChallenge: Large-scale Real-robot Evaluation of Embodied Policies
Adina Yakefu, Bin Xie, Chongyang Xu +34
Testing on real machines is indispensable for robotic control algorithms. In the context of learning-based algorithms, especially VLA models, demand for large-scale evaluation, i.e…