48 citations · 136 across the 10 of their papers we have counts for
5 papers · 1 filter
Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions
Charles Dawson, Zengyi Qin, Sicun Gao +1
Safety and stability are common requirements for robotic control systems; however, designing safe, stable controllers remains difficult for nonlinear and uncertain models. We devel…
Reactive and Safe Road User Simulations using Neural Barrier Certificates
Yue Meng, Zengyi Qin, Chuchu Fan
Reactive and safe agent modelings are important for nowadays traffic simulator designs and safe planning applications. In this work, we proposed a reactive agent model which can en…
Density Constrained Reinforcement Learning
Zengyi Qin, Yuxiao Chen, Chuchu Fan
We study constrained reinforcement learning (CRL) from a novel perspective by setting constraints directly on state density functions, rather than the value functions considered by…
MonoGRNet: A General Framework for Monocular 3D Object Detection
Zengyi Qin, Jinglu Wang, Yan Lu
Detecting and localizing objects in the real 3D space, which plays a crucial role in scene understanding, is particularly challenging given only a monocular image due to the geomet…
Learning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates
Zengyi Qin, Kaiqing Zhang, Yuxiao Chen +2
We study the multi-agent safe control problem where agents should avoid collisions to static obstacles and collisions with each other while reaching their goals. Our core idea is t…