Forward models applied in visual servoing for a reaching task in the iCub humanoid robot

Article type: Research Article

Authors: Gamarra, Daniel Fernando Tello | Pinpin, Lord Kenneth | Laschi, Cecilia | Dario, Paolo

Affiliations: Scuola Superiore Sant'Anna, ARTS Lab (Advanced Robotics Technology and Systems Laboratory), V.le Rinaldo Piaggio, 34-56025 Pontedera (PI), Italy

Note: [] Corresponding author: Email: fgamarra@sssup.it; d.tellogamarra@sssup.it

Abstract: This paper details the application of a forward model to improve a reaching task. The reaching task must be accomplished by a humanoid robot with 53 degrees of freedom (d.o.f.) and a stereo-vision system. We have explored via simulations a new way of constructing and utilizing a forward model that encodes eye–hand relationships. We constructed a forward model using the data obtained from only a single reaching attempt. ANFIS neural networks are used to construct the forward model, but the forward model is updated online with new information that comes from each reaching attempt. Using the obtained forward model, an initial image Jacobian is estimated and is used with a visual servoing controller. Simulation results demonstrate that errors are lower when the initial image Jacobian is derived from the forward model. This paper is one of the few attempts at applying visual servoing in a complete humanoid robot.

Keywords: forward models, ANFIS, robotics, visual servoing, neural networks

DOI: 10.1080/11762320903180849

Journal: Applied Bionics and Biomechanics, vol. 6, no. 3-4, pp. 345-354, 2009