报告会题目：Robotic navigation: from vector fields to chatGPT
Ming Cao is the director of the Jantina Tammes School of Digital Society, Technology and AI, and a professor of networks and robotics at the University of Groningen, the Netherlands. He received the Bachelor degree in 1999 and the Master degree in 2002 from Tsinghua University, China, and the Ph.D. degree in 2007 from Yale University, USA, all in Electrical Engineering. From 2007 to 2008, he was a Research Associate at Princeton University, USA. He worked as a research intern in 2006 at the IBM T. J. Watson Research Center, USA. He is the 2017 and inaugural recipient of the Manfred Thoma medal from the International Federation of Automatic Control (IFAC) and the 2016 recipient of the European Control Award sponsored by the European Control Association (EUCA). He is an IEEE fellow. He is a Senior Editor for Systems and Control Letters, an Associate Editor for IEEE Transactions on Automatic Control, IEEE Transactions on Control of Network Systems and IEEE Robotics and Automation Magazine, and was an Associate Editor for IEEE Transactions on Circuits and Systems and IEEE Circuits and Systems Magazine. He is a member of the IFAC Council. His research interests include autonomous agents and multi-agent systems, complex networks and decision-making processes.
Robotic navigation is a fundamental function for mobile robots carrying out environmental monitoring and sampling tasks. In this talk, I show how to design guiding vector fields to enable motion coordination among robots that follow a given path that may self-intersect and thus become challenging for standard control algorithms; I also show how to construct composite guiding vector fields to avoid colliding with obstacles of arbitrary shapes. Both theoretical guarantees and experimental validations are discussed for practical scenarios. Given the growing interest in generative AI, I will also show how chatbot can be a potential new tool for robotic navigation.