|公告標題||演講公告:Computational Methods for Robot Shepherding|
演講主題：Computational Methods for Robot Shepherding
摘要：Algorithms for the control and monitoring of swarms of moving agents are important in a wide variety of real and virtual applications such as crowd control, livestock herding, and decentralized robot control architecture. In the presence of obstacles, these applications can be quite difficult, especially with large swarms. In this talk, I will present reusable and robust motion planning algorithms for the swarm control problem of shepherding, a task involving using a small set of mobile robots interact with a larger set of swarm agents; and the swarm monitoring problem of visibility-based pursuit, a task involving using a mobile robot to follow and maintain visibility of a moving swarm. For both problems, I will discuss algorithms that can efficiently sample reusable geometric information in the environment to enable fast online planning and replanning. The talk will end with our results using multi-agent simulation software to understand the tradeoffs between different techniques for these problems.
Jyh-Ming Lien is an Associate Professor in the Department of Computer
Science at George Mason University and a Research Professor at Ewha Womans University in Seoul, Korea. He is the director of the Motion and Shape Computing (MASC) group and affiliated with the Autonomous Robotics Laboratory. He received his B.S in Computer Science from National Cheng-Chi University, Ph.D. in Computer Science from Texas A&M University in 2006. Prior to joining George Mason in 2007, he was a postdoctoral researcher at UC Berkeley. His research goal is to develop efficient, robust and practical algorithms for representing, manipulating and analyzing massive geometric data of shape and motion. His research finds applications in the areas of computational geometry, computer graphics, GIS, visualization and robotics.
His research has been supported by NSF, USGS, DOT, AFOSR, and Virginia Center for Innovative Technology. Images, videos, papers, and software about his work can be found at: https://masc.cs.gmu.edu/