l 2022年6月9日（周四） 腾讯会议：814-653-653
报告嘉宾：Prof.Jingjin Yu，Department of Computer Science, Rutgers University at New Brunswick.
报告题目：Multi-Robot Path Planning on Graphs
报告摘要：Multi-robot systems have seen wide adoptions in domains including logistics (e.g., warehouses) and service industries (drone shows). In this talk, I will discuss some of our efforts in enabling large fleets of robots to efficiently work together. Specifically, the problem of optimal multi-robot path planning (MRPP) is examined in a graph-theoretic setting. I will start with the complexity aspect of MRPP problems, showing that they are generally NP-hard to optimally solve. Contrasting the hardness results, I will present our recent work in which we developed algorithms that can compute 1.x optimal solutions in polynomial time. In particular, our algorithms are highly scalable, applying to dense settings with over 50000 robots. Lastly, I will discuss a different line of algorithms based on integer programming that is easy to use and fairly fast, and show some of its applications in academia.
报告人简介：Jingjin Yu is an Associate Professor in the Department of Computer Science, Rutgers University at New Brunswick. He received his B.S. from the University of Science and Technology of China, and obtained his M.S. in Computer Science and Ph.D. in Electrical and Computer Engineering, both from the University of Illinois, where he briefly stayed as a postdoctoral researcher. Before joining Rutgers, he was a postdoctoral researcher at the Massachusetts Institute of Technology. He is broadly interested in the area of algorithmic robotics, focusing on issues related to optimality, complexity, and the design of efficient decision-making methods. He is a recipient of the NSF CAREER award and an Amazon Research Award.