Robot Programming by Demonstration

This project is concerned with the design of robust and flexible controllers to drive learning of abstract and goal-directed imitation tasks in a multi-degrees of freedom humanoid robot. The imitation tasks include manipulation of objects and the reproduction of abstract and communicative gestures. Biological principles can improve the design of learning systems for robot programming through demonstration. This project takes inspiration in biology to develop controllers that show similar robustness and flexibility as that found in humans.

Research:

	Learning Task Constraints
	Dynamical Control
	General Inverse Kinematics