papers

Publications (12)

eess.SY2023

Learning to Seek: Multi-Agent Online Source Seeking Against Non-Stochastic Disturbances

Bin Du, Kun Qian, Christian Claudel +1

This paper proposes to leverage the emerging~learning techniques and devise a multi-agent online source {seeking} algorithm under unknown environment. Of particular significance in…

eess.SY2020

Control Protocol Design and Analysis for Unmanned Aircraft System Traffic Management

Jiazhen Zhou, Dawei Sun, Inseok Hwang +1

Due to the rapid development technologies for small unmanned aircraft systems (sUAS), the supply and demand market for sUAS is expanding globally. With the great number of sUAS rea…

cs.RO2026

City-Wide Low-Altitude Urban Air Mobility: A Scalable Global Path Planning Approach via Risk-Aware Multi-Scale Cell Decomposition

Josue N. Rivera, Dengfeng Sun, Chen Lv

The realization of Urban Air Mobility (UAM) necessitates scalable global path planning algorithms capable of ensuring safe navigation within complex urban environments. This paper…

eess.SY2025

Receding Hamiltonian-Informed Optimal Neural Control and State Estimation for Closed-Loop Dynamical Systems

Josue N. Rivera, Dengfeng Sun

This paper formalizes Hamiltonian-Informed Optimal Neural (Hion) controllers, a novel class of neural network-based controllers for dynamical systems and explicit non-linear model-…

cs.RO2021

Multi-Robot Dynamical Source Seeking in Unknown Environments

Bin Du, Kun Qian, Christian Claudel +1

This paper presents an algorithmic framework for the distributed on-line source seeking, termed as 'DoSS', with a multi-robot system in an unknown dynamical environment. Our algori…

cs.RO2026

Beyond Self-Play: Hierarchical Reasoning for Continuous Motion in Closed-Loop Traffic Simulation

Weifan Zhang, Xiaofeng Zhao, Adel Bazzi +3

Closed-loop traffic simulation requires agents that are both scalable and behaviorally realistic. Recent self-play reinforcement learning approaches demonstrate strong scalability,…