Autonomous learning of 3D reaching in a humanoid robot

— In this paper, we describe the implementation of a precise reaching controller on an upper-torso humanoid robot. The solution we propose does not rely on prior models of the kinematic structure of either the arm or the head. A learning strategy enables the robot to acquire the required sensory-motor transformations. After learning the robot is able to precisely reach for a visually identified object in the 3-dimensional space. In this technique we use the fixation point (represented in the head joints motor space) as a reference frame to code the position of the object and to represent the eye-to-hand Jacobian matrix. This strategy successfully deals with the kinematic redundancy of the structure and constraints the dimensionality of the problem.

• Type: Conference
• Year: 2007
• Where: IROS
• Authors: Francesco Nori, Lorenzo Natale, Giulio Sandini, Giorgio Metta
• Keywords: IROS 2007, Precise Reaching Controller, Required Sensory-motor Transformations, Robotics, Upper-torso Humanoid Robot