Synopsis
This book provides a thorough overview of the state-of-the-art field-programmable gate array (FPGA)-based robotic computing accelerator designs and summarizes their adopted optimized techniques. This book consists of ten chapters, delving into the details of how FPGAs have been utilized in robotic perception, localization, planning, and multi-robot collaboration tasks. In addition to individual robotic tasks, this book provides detailed descriptions of how FPGAs have been used in robotic products, including commercial autonomous vehicles and space exploration robots.
À propos de l?auteur
Dr. Shaoshan Liu is founder and CEO of PerceptIn Inc., a company focusing on developing autonomous driving technologies. Dr. Liu has published more than 70 research papers, 40 U.S. patents, and over 150 international patents on autonomous driving technologies and robotics, as well as 2 books on autonomous driving technologies: Creating Autonomous Vehicle Systems (Morgan & Claypool) and Engineering Autonomous Vehicles and Robots: The DragonFly Modular-Based Approach (Wiley–IEEE). He is a senior member of IEEE, a Distinguished Speaker of the IEEE Computer Society, a Distinguished Speaker of ACM, and a founder of the IEEE Special Technical Community on Autonomous Driving Technologies. Dr. Liu received a Master's of Public Administration (MPA) from Harvard Kennedy School and a Ph.D. in Computer Engineering from University of California, Irvine.
Zishen Wan received his M.S. degree from Harvard University, Cambridge, MA, USA, in 2020 and his B.S. degree from Harbin Institute of Technology, Harbin, China, in 2018, both in electrical engineering. He is currently pursuing a Ph.D. in Electrical and Computer Engineering from Georgia Institute of Technology, Atlanta, GA, USA. He has a broad research interest in VLSI design, computer architecture, machine learning, and edge intelligence, with a focus on energy-efficiency, robust hardware, and system design for autonomous machines. He has received the Best Paper Award in DAC 2020 and CAL 2020.
Dr. Bo Yu received his B.S. degree in Electronic Technology and Science from Tianjin University, Tianjin, China, in 2006, and a Ph.D. degree from the Institute of Microelectronics, Tsinghua University, Beijing, China, in 2013. He is currently the CTO of PerceptIn Inc., a company focusing on providing visual perception solutions for robotics and autonomous driving. His current research interests include algorithm and systems for robotics and autonomous vehicles. Dr. Yu is also a Founding Member of the IEEE Special Technical Community on Autonomous Driving and a senior member of IEEE. Dr. Yu Wang received his B.S. degree in 2002 and Ph.D. (with honor) in 2007 from Tsinghua University, Beijing, China. He is currently a Tenured Professor and Chair with the Department of Electronic Engineering, Tsinghua University. His research interests include application-specific hardware computing, parallel circuit analysis, and power/reliability aware system design methodology. Dr. Wang has authored and coauthored over 250 papers in refereed journals and conferences. He has received Best Paper Award in ASPDAC 2019, FPGA 2017, NVMSA17, ISVLSI 2012, and Best Poster Award in HEART 2012 with 9 Best Paper Nominations. He is a recipient of DAC Under-40 Innovator Award in 2018. He served as TPC chair for ICFPT 2019, ISVLSI 2018, ICFPT 2011 and Finance Chair of ISLPED 2012-2016, and served as the program committee member for leading conferences in EDA/FPGA area. Currently he serves as Associate Editor for IEEE Transasctions on CAS for Video Technology, IEEE Transactions on CAD, and ACM TECS. He is an IEEE/ACM senior member. He is the co-founder of Deephi Tech (acquired by Xilinx in 2018), which is a leading deep learning computing platform provider.
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