Collaborative Fleet Maneuvering for Multiple Autonomous Vehicle Systems

Yuanzhe Wang received the B.Eng. degree from the Southeast University, China, in 2010, the M.Eng. degree from the Beihang University, China, in 2013, and the Ph.D. degree from the Nanyang Technological University (NTU), Singapore, in 2019. He is a Research Fellow in the School of Electrical and Electronic Engineering, NTU. He has served as an Associate Editor for The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) from 2020 to 2022. His current research interests include mobile robotics, control application, and cybersecurity in robotics. Danwei Wang received his Ph.D. and M.S.E. degrees from the University of Michigan, Ann Arbor in 1989 and 1984, respectively. He received his B.E. degree from the South China University of Technology, China, in 1982. He is a Professor in the School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore. He has served as the Head of the Division of Control and Instrumentation, NTU from 2005 to 2011, the Director of the Center for System Intelligence and Efficiency, NTU from 2014 to 2016, and the Director of the ST Engineering-NTU Corporate Laboratory, NTU from 2015 to 2021. He also served as general chairman, technical chairman and various positions in several international conferences. He was a recipient of Alexander von Humboldt fellowship, Germany. He is a Fellow of Academy of Engineering, Singapore, and a Fellow of IEEE. His research interests include robotics, control engineering, and fault diagnosis.

• Introduction.- Technical Background.- Anchor-Based Flexible Fleet Maneuvering.- Map-Based Virtual-Structure Fleet Maneuvering in Cluttered Environments.- Vision-Based Leader-Follower Queue Maneuvering in Unknown Cluttered Environments.- Vision-Based Flexible Fleet Maneuvering in Unknown Cluttered Environments.- Map Matching Based Leader-Follower Path Retracing in Infrastructure-Free Environments.- Multi-UAV Optimal Fleet Flying for Air Patrol in Constrained Environments.- Conclusion.