Our guiding principle to teach robots new tasks is to take inspiration from the way humans learn new skills by imitation. Robot learning by imitation learning, also referred to as programming by demonstration, is the concept of having a robot observe a human instructor performing a task and imitate it when needed. We rely on this paradigm for robot programming as a powerful tool to accelerate learning in highly complex motor systems, such as humanoid robots.
Main scientific issues in this research area are the capturing of human daily actions, the modeling and representation of human actions, the connection between learning low-level representations with learning high-level representations leading to generalization of different context. Furthermore, we are investigating how to combine imitation and exploration in a single interaction paradigm where imitation is not only used as a starting point for search, but where the user remains closely involved in the acquisition of new skills by evaluating new solutions experimented by the robot or by providing additional examples to accelerate the learning process when the robot is stuck in an unknown situation