Abstract. Exploring the full potential of humanoid robots requires their ability to learn, generalize and reproduce complex tasks that will be faced in dynamic environments. In recent years, significant attention has been devoted to recovering kinematic information from the human motion using a motion capture system. This paper demonstrates and evaluates the use of a Kinectbased capture system that estimates the 3D human poses and converts them into gestures imitation in a robot. The main objectives are twofold: (1) to improve the initially estimated poses through a correction method based on constraint optimization, and (2) to present a method for computing the joint angles for the upper limbs corresponding to motion data from a human demonstrator. The feasibility of the approach is demonstrated by experimental results showing the upper-limb imitation of human actions by a robot model.

No abstract

No abstract

No abstract