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

College

Gokongwei College of Engineering

Department/Unit

Manufacturing Engineering and Management

Document Type

Article

Source Title

Applied Bionics and Biomechanics

Volume

6

Issue

3

First Page

345

Last Page

354

Publication Date

2009

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.

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Disciplines

Artificial Intelligence and Robotics

Keywords

Androids; Robotics; Neural networks (Computer science); Servomechanisms

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