Learning based robot control with sequential Gaussian process
Sooho Park, Shabbir Kurbanhusen Mustafa, Kenji Shimada · 2013
In recent years, robots have started being utilized in applications with complex/unknown interaction environment, which makes system/interface modeling to be very challenging. In order to meet the demand from such applications, the experience based learning approach can be a suitable tool. In this paper, a general algorithm for learning based robot control is presented, and a novel online algorithm using sequential Gaussian process is introduced. As a case study, a simple inverted pendulum is tested to present the capabilities of the proposed algorithm.