Kwang-Cheng Chen, IEEE Fellow, Professor

University of South Florida, Tampa, Florida, USA

Title: Real-Time Multi-Robot Task Assignment in a Wireless Networked Smart Factory


Kwang-Cheng Chen has been a Professor at the Department of Electrical Engineering, University of South Florida, since 2016. From 1987 to 2016, Dr. Chen worked with SSE, Communications Satellite Corp., IBM Thomas J. Watson Research Center, National Tsing Hua University, HP Labs., and National Taiwan University in mobile communications and networks. He visited TU Delft (1998), Aalborg University (2008), Sungkyunkwan University (2013), and Massachusetts Institute of Technology (2012-2013, 2015-2016).  He founded a wireless IC design company in 2001, which was acquired by MediaTek Inc. in 2004. He has been actively involving in the organization of various IEEE conferences and serving editorships with several IEEE journals, together with various IEEE volunteer services to the IEEE, Communications Society, Vehicular Technology Society, and Signal Processing Society, such as founding the Technical Committee on Social Networks in the IEEE Communications Society. He also serves in the editorial board of Nature Scientific Reports. Dr. Chen also has contributed essential technology to various international standards, namely IEEE 802 wireless LANs, Bluetooth, LTE and LTE-A, 5G-NR, and ITU-T FG ML5G. He has authored and co-authored over 300 IEEE papers (including 7 Highly Cited Papers in past 10 years), 4 books published by Wiley and River (most recently, Artificial Intelligence in Wireless Robotics, 2020), and 26 granted US patents. Dr. Chen is an IEEE Fellow and has received several prestigious awards including 2011 IEEE COMSOC WTC Recognition Award, 2014 IEEE Jack Neubauer Memorial Award, 2014 IEEE COMSOC AP Outstanding Paper Award. Dr. Chen’s current research interests include wireless networks, quantum computations and communications, artificial intelligence and multi-agent systems, blockchain, and post-quantum cryptography.


Smart factory emerges as one of the most influential technologies for Internet of Things, which holistically integrates wireless networking, AI computing, and automatic control to accomplish flexible production. We propose a novel model for a smart factory as two kinds of multi-robot systems, production robots and transportation robots. Focusing on production robots, real-time algorithm of multi-robot task assignment is first proposed to enable flexible re-configuration of a smart factory according to dynamic demands. To facilitate resilient operation of production multi-robot system that can be viewed as a cyber-physical system, social learning is uniquely employed to maintain the high yield of precision production against point failures including errors due to wireless communications. This series of technology innovations may present world’s first computationally efficient solution to realize a smart factory.