演讲人：Kun Li    California Institute of Technology

题  目：Inverse Reinforcement Learning from Sparse High-Dimensional Motion Data in Robotic Applications

时  间：2018年5月7日下午14: 00

地  点：哈工大深圳研究生院A406

讲座内容:

This talk presents the application of inverse reinforcement learning to evaluating human motion and teaching robot tasks. The main difficulties are the high-dimensional and insufficient data. To solve the problem, this talk introduces two algorithms to handle the data dimensions and data sparsity. The resultant algorithms are used to evaluate the skills of surgical robot operators, quantify the effects of therapies, and teach robot simple grasping tasks. At last, some ongoing and future works are presented.

Kun Li：

Kun Li got his BS degree from Jilin University, China in 2010, and his PhD degree from The Chinese University of Hong Kong in 2015. Since then, he is a postdoctoral scholar in California Institute of Technology. His main research interests are robot learning and robot vision, especially 3D visual data processing and robot imitation learning via inverse reinforcement learning.