3 papers
cs.RO2026
Dynamics Are Learned, Not Told: Semi-Supervised Discovery of Latent Dynamics Geometries For Zero-Shot Policy Adaptation
Zhiming Xu, Weitao Zhou, Xianghui Pan +4
Real-world dynamics shifts pose a critical challenge for reinforcement learning in robotics, as policies tightly coupled to nominal environments often fail catastrophically when ph…
cs.RO2026
LSRE: Latent Semantic Rule Encoding for Real-Time Semantic Risk Detection in Autonomous Driving
Qian Cheng, Weitao Zhou, Cheng Jing +5
Real-world autonomous driving must adhere to complex human social rules that extend beyond legally codified traffic regulations. Many of these semantic constraints, such as yieldin…
cs.RO2025
Dynamically Local-Enhancement Planner for Large-Scale Autonomous Driving
Nanshan Deng, Weitao Zhou, Bo Zhang +4
Current autonomous vehicles operate primarily within limited regions, but there is increasing demand for broader applications. However, as models scale, their limited capacity beco…