no code implementations • 12 Apr 2023 • Qingchen Liu, Zengjie Zhang, Nhan Khanh Le, Jiahu Qin, Fangzhou Liu, Sandra Hirche
This paper proposes a novel distributed coverage controller for a multi-agent system with constant-speed unicycle robots (CSUR).
no code implementations • 13 Jan 2023 • Zengjie Zhang, Qingchen Liu, Mohammad H. Mamduhi, Sandra Hirche
Quantifying the average communication rate (ACR) of a networked event-triggered stochastic control system (NET-SCS) with deterministic thresholds is challenging due to the non-stationary nature of the system's stochastic processes.
no code implementations • 20 Jun 2021 • Nhan Khanh Le, Yang Liu, Quang Minh Nguyen, Qingchen Liu, Fangzhou Liu, Quanwei Cai, Sandra Hirche
Federated learning is the distributed machine learning framework that enables collaborative training across multiple parties while ensuring data privacy.
no code implementations • 9 Jun 2021 • Cong Li, Zengjie Zhang, Ahmed Nesrin, Qingchen Liu, Fangzhou Liu, Martin Buss
This paper presents an integrated perception and control approach to accomplish safe autonomous navigation in unknown environments.
no code implementations • 4 May 2021 • Cong Li, Yongchao Wang, Fangzhou Liu, Qingchen Liu, Martin Buss
This paper presents a new formulation for model-free robust optimal regulation of continuous-time nonlinear systems.
no code implementations • 7 Apr 2021 • Siyi Wang, Qingchen Liu, Precious Ugo Abara, John S. Baras, Sandra Hirche
In this paper, we study the trade-off between the transmission cost and the control performance of the multi-loop networked control system subject to network-induced delay.
no code implementations • 29 Mar 2021 • Zewen Yang, Stefan Sosnowski, Qingchen Liu, Junjie Jiao, Armin Lederer, Sandra Hirche
In this paper, a distributed learning leader-follower consensus protocol based on Gaussian process regression for a class of nonlinear multi-agent systems with unknown dynamics is designed.
no code implementations • 10 Jun 2020 • Cong Li, Qingchen Liu, Zhehua Zhou, Martin Buss, Fangzhou Liu
By introducing pseudo controls and risk-sensitive input and state penalty terms, the constrained robust stabilization problem of the original system is converted into an equivalent optimal control problem of an auxiliary system.