Collaborative Perception, Localization and Mapping for Autonomous Systems

Yufeng Yue received the B.Eng. degree in automation from Beijing Institute of Technology, Beijing, China, in 2014, the Ph.D. degree from Nanyang Technological University, Singapore, in 2019. He was a visiting scholar with University of California, Los Angeles in 2019. He served as a research fellow with School of Electrical and Electronic Eng., Nanyang Technological University, Singapore, from 2018 to 2020.  He is currently an associate professor with School of Automation, Beijing Institute of Technology, Beijing, China. His research interests include perception, mapping and navigation for collaborative autonomous systems in complex environments. Danwei Wang is leading the autonomous mobile robotics research group. He received his Ph.D and MSE 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. Since 1989, he has been with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. Currently, he is professor and the co-director of the ST Engineering – NTU Corporate Laboratory. He is a senator in NTU Academics Council. He has served as general chairman, technical chairman and various positions in international conferences, such as ICARCV and IROS conferences. He is an associate editor for the International Journal of Humanoid Robotics and served as an associate editor of Conference Editorial Board, IEEE Control Systems Society from 1998 to 2005. He was a recipient of Alexander von Humboldt fellowship, Germany. His research interests include robotics, control theory and applications.

Introduction.- Technical Background.- Point Registration Approach for Map Fusion.- Submap-Based Probabilistic Inconsistency Detection.- Hierarchical Map Fusion Framework with Homogeneous Sensors.-  Collaborative 3D Mapping using Heterogeneous Sensors.- All-Weather Collaborative Mapping with Dynamic Objects.- Collaborative Probabilistic Semantic Mapping using CNN.