Gesture learning and execution in a humanoid robot via dynamic movement primitives ?
A system for learning and executing gestures in a humanoid robot has been developed. Gestures are represented via the use of DMPs on the robotic platform REEM. Agnostic knowledge is considered, so our approach can be easily extended. Gestures can be recorded with different procedures: robot, user, or external devices. Experiments show how knowledge is acquired, represented, generalized and reproduced.
humanoid robot dynamic movement primitives knowledge acquisition gesture representation