Dynamics model abstraction scheme using radial basis functions
type: Item
instance of: scholarly article
title: Dynamics model abstraction scheme using radial basis functions
zbMATH Open document ID: 1248.93018
DOI: 10.1155/2012/761019
author: Silvia Tolu
author: Mauricio Vanegas
author: Rodrigo Agís
author: Richard Carrillo
author: Antonio Cañas
published in: Journal of Control Science and Engineering
publication date: 2012-09-06T00:00:00Z
review text: Summary: This paper presents a control model for object manipulation. Properties of objects and environmental conditions influence the motor control and learning. System dynamics depend on an unobserved external context, for example, work load of a robot manipulator. The dynamics of a robot arm change as it manipulates objects with different physical properties, for example, the mass, shape, or mass distribution. We address active sensing strategies to acquire object dynamical models with a Radial Basis Function (RBF) neural network. Experiments are done using a real robot's arm, and trajectory data are gathered during various trials manipulating different objects. Biped robots do not have high force joint servos and the control system hardly compensates all the inertia variation of the adjacent joints and disturbance torque on dynamic gait control. In order to achieve smoother control and lead to more reliable sensorimotor complexes, we evaluate and compare a sparse velocity-driven versus a dense position-driven control scheme.
Mathematics Subject Classification ID: 93A30
Mathematics Subject Classification ID: 92B20
Mathematics Subject Classification ID: 93C95
zbMATH DE Number: 6078170
zbMATH Keywords: control model for object manipulation
zbMATH Keywords: motor control and learning
zbMATH Keywords: robot manipulator
zbMATH Keywords: active sensing strategies
zbMATH Keywords: radial basis function (RBF) neural network: velocity-driven versus a dense position-driven control scheme.
Wikidata QID: Q58908024
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/761019
OpenAlex ID: W2070008767
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description: scientific article; zbMATH DE number 6078170