报告摘要：
Artificial intelligence has recently been used to design and optimize robotic controllers to accomplish human-like performance or super-human performan by using data-driven approaches. This talk will introduce our recent work on how to use machine learning techniques to compute high-quality feedback controllers for several typical applications, including the distributed multi-robot navigation, robot-crowd interaction, deformable object manipulation, and unmanned digger.

 

报告人简介：
Jia Pan received his Ph.D. degree in Computer Science from the University of North Carolina at Chapel Hill in 2013. He has been with the City University of Hong Kong since 2015. His research interests include robotics and artificial intelligence.