Imitation-based Skill Learning Simulator for Mobile Robots

In this text, a framework that allows a layperson to transfer skills to a simulated robot is developed. The simulated robot is played by a simulated truck with a trailer. The elements that make up the framework are imitation-based learning and primitives that describe the robot s motions. The skill transfer is accomplished using imitation learning where the demonstrated movements are mapped to a set of primitives, which are combined in a desired sequence to implement novel skills. In this monograph, imitation technology is developed in a simple two-dimensional world of a truck. Enabling technologies for this simple world will be very similar to the technologies that will enable manufacturing, assembly, and maintenance as well as service robots to utilize imitation learning. Creating a framework to transfer skills to robots that could be used by lay people would have a tremendous effect on our everyday lives. The effect would be similar to the effect that software applications for PCs had on our society.

Autorentext

Mohammad H. Salah is an assistant professor in the department of Mechatronics Engineering at the Hashemite University, Jordan. Dr. Salah received the Ph.D. degree (2007) in electrical engineering from Clemson University, SC, USA. His research interests are in the application of nonlinear control techniques for mechatronic systems.