Imitation Learning of Positional and Force Skills Demonstrated via Kinesthetic Teaching and Haptic Input

A method to learn and reproduce robot force interactions in a Human-Robot Interaction setting is proposed. The method allows a robotic manipulator to learn to perform tasks which require exerting forces on external objects by interacting with a human operator in an unstructured environment. This is achieved by learning two aspects of a task: positional and force profiles. The positional profile is obtained from task demonstrations via kinesthetic teaching. The force profile is obtained from additional demonstrations via a haptic device. A human teacher uses the haptic device to input the desired forces which the robot should exert on external objects during the task execution. The two profiles are encoded as a mixture of dynamical systems, which is used to reproduce the task satisfying both the positional and force profiles. An active control strategy based on task-space control with variable stiffness is then proposed to reproduce the skill. The method is demonstrated with two experiments in which the robot learns an ironing task and a door opening task. keywords: imitation learning, kinesthetic teaching, programming by demonstration, pHRI, haptics