8 papers
Slow Brain, Fast Planner: Latency-Resilient VLM-Augmented Urban Navigation
Zhenghao "Mark'' Peng, Honglin He, Quanyi Li +2
Learning-based planners for sidewalk navigation can generate diverse candidate trajectories in real time, yet their scoring functions often fail to select the best trajectory in ch…
VLAs are Confined yet Capable of Generalizing to Novel Instructions
Quanyi Li
Vision-language-action models (VLAs) often achieve high performance on demonstrated tasks but struggle significantly when required to extrapolate, combining skills learned from dif…
Grounded World Model for Semantically Generalizable Planning
Quanyi Li, Lan Feng, Haonan Zhang +4
In Model Predictive Control (MPC), world models predict the future outcomes of various action proposals, which are then scored to guide the selection of the optimal action. For vis…
RAP: 3D Rasterization Augmented End-to-End Planning
Lan Feng, Yang Gao, Eloi Zablocki +5
Imitation learning for end-to-end driving trains policies only on expert demonstrations. Once deployed in a closed loop, such policies lack recovery data: small mistakes cannot be…
A Simple Framework Towards Vision-based Traffic Signal Control with Microscopic Simulation
Pan He, Quanyi Li, Xiaoyong Yuan +1
Traffic signal control (TSC) is crucial for reducing traffic congestion leading to smoother traffic flow, reduced idle time, and mitigated CO2 emissions. In this paper, we explore…
Towards Autonomous Micromobility through Scalable Urban Simulation
Wayne Wu, Honglin He, Chaoyuan Zhang +5
Micromobility, which utilizes lightweight mobile machines moving in urban public spaces, such as delivery robots and mobility scooters, emerges as a promising alternative to vehicu…