Track 3

Prof. Zhongliang Zhao

Beihang University, China




Biography: Zhongliang Zhao is a Professor at Beihang University (BUAA), China. He got his Ph.D. degree in Computer Science from the University of Bern, Switzerland in 2014. His current research interests include machine learning, ad-hoc networks, intelligent unmanned system, and space-terrestrial integrated networks.

 

Assoc. Prof. Yongcai Wang

Renmin University of China, China




Biography: Yongcai Wang received his BS and PhD degrees from department of automation sciences and engineering, Tsinghua University in 2001 and 2006 respectively. He worked as associated researcher at NEC Labs. China from 2007-2009. He was a research scientist in Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University from 2009-2015. He was a visiting scholar at Cornell University in 2015. He is currently an associate professor at Department of Computer Sciences, Renmin University of China. He has published more than 80 papers on famous international conferences and journals, including TMC, TON, JSAC, Infocom, TCS etc. He won the First Prize of Technical Invention of China Navigation Society in 2021. His research interests include network localization, network algorithms, cooperative localization and mapping algorithms.
Speech Title: Theory and Algorithms for Relative Location Estimation in UAV Networks
Abstract: Relative localization plays a critical role in UAV network formation control and other applications. Regarding the different types of sensors equipped on the UAVs, UAV relative localization can be carried out by UWB-based, Range-Only Relative Localization (RORL) or by Vision-UWB cooperated, 6-DOF Relative State Estimation (VRSE). Because the UAV network is generally sparse, localizability problem and accurate localization algorithms are both important. In this talk, I will introduce our recent research progress on the localizability theories and relative localization algorithms for both RORL and VRSE problems. In RORL problem, we present efficient algorithm to detect the localizable components in sparse UAV networks and efficient component-stitching based algorithm for RORL. In VRSE, we present the relative state estimation model and efficient localization algorithm.


Prof. Zheng Dong

Shandong University, China




Biography: Zheng Dong (M’ 18) received the B.Sc. and M.Eng. degrees from the School of Information Science and Engineering, Shandong University, Jinan, China, in 2009 and 2012, respectively, and the Ph.D. degree from the Department of Electrical and Computer Engineering, McMaster University, Canada, in 2016. He was a Postdoc Research Fellow in the School of Electrical and Information Engineering, The University of Sydney, Australia. He is currently a Research Professor in the School of Information Science and Engineering, Shandong University, China. His research interests include the Industrial Internet of Things and ultra-reliable low-latency communications.