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Applied Bionics and Biomechanics
Volume 6, Issue 3-4, Pages 345-354

Forward Models Applied in Visual Servoing for a Reaching Task in the iCub Humanoid Robot

Daniel Fernando Tello Gamarra, Lord Kenneth Pinpin, Cecilia Laschi, and Paolo Dario

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

Received 26 May 2009

Copyright © 2009 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.