On the Ecological Approach to Information and Control for Roboticists

The ongoing and increasingly important trend in robotics to conceive designs that decentralize control is paralleled by currently active research paradigms in the study of perception and action. James Gibson's ecological approach is one of these paradigms. Gibson's approach emerged in part...

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Main Authors: Jorge Ibáñez-Gijón, Alex Díaz, Lorena Lobo, David M. Jacobs
Format: Article
Language:English
Published: SAGE Publishing 2013-06-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.5772/55671
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spelling doaj-afc9bd592a8d478bb92cffcde69830d42020-11-25T03:43:31ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142013-06-011010.5772/5567110.5772_55671On the Ecological Approach to Information and Control for RoboticistsJorge Ibáñez-Gijón0Alex Díaz1Lorena LoboDavid M. Jacobs2 Faculty of Psychology, Autonomous University of Madrid, Spain Faculty of Psychology, Autonomous University of Madrid, Spain Faculty of Psychology, Autonomous University of Madrid, SpainThe ongoing and increasingly important trend in robotics to conceive designs that decentralize control is paralleled by currently active research paradigms in the study of perception and action. James Gibson's ecological approach is one of these paradigms. Gibson's approach emerged in part as a reaction to representationalist and computationalist approaches, which devote the bulk of their resources to the study of internal processes. The ecological approach instead focuses on constraints and ambient energy patterns in the animal-environment coalition. The present article reviews how the emphasis on the environment by ecological psychologists has given rise to the concepts of direct perception, higher order information, active information pick up, information-based control laws, prospective control, and direct learning. Examples are included to illustrate these concepts and to show how they can be applied to the construction of robots. Action is described as emergent and self-organized. It is argued that knowledge about perception, action, and learning as it occurs in living organisms may facilitate the construction of robots, more obviously so if the aim is to construct (to some extent) biologically plausible robots.https://doi.org/10.5772/55671
collection DOAJ
language English
format Article
sources DOAJ
author Jorge Ibáñez-Gijón
Alex Díaz
Lorena Lobo
David M. Jacobs
spellingShingle Jorge Ibáñez-Gijón
Alex Díaz
Lorena Lobo
David M. Jacobs
On the Ecological Approach to Information and Control for Roboticists
International Journal of Advanced Robotic Systems
author_facet Jorge Ibáñez-Gijón
Alex Díaz
Lorena Lobo
David M. Jacobs
author_sort Jorge Ibáñez-Gijón
title On the Ecological Approach to Information and Control for Roboticists
title_short On the Ecological Approach to Information and Control for Roboticists
title_full On the Ecological Approach to Information and Control for Roboticists
title_fullStr On the Ecological Approach to Information and Control for Roboticists
title_full_unstemmed On the Ecological Approach to Information and Control for Roboticists
title_sort on the ecological approach to information and control for roboticists
publisher SAGE Publishing
series International Journal of Advanced Robotic Systems
issn 1729-8814
publishDate 2013-06-01
description The ongoing and increasingly important trend in robotics to conceive designs that decentralize control is paralleled by currently active research paradigms in the study of perception and action. James Gibson's ecological approach is one of these paradigms. Gibson's approach emerged in part as a reaction to representationalist and computationalist approaches, which devote the bulk of their resources to the study of internal processes. The ecological approach instead focuses on constraints and ambient energy patterns in the animal-environment coalition. The present article reviews how the emphasis on the environment by ecological psychologists has given rise to the concepts of direct perception, higher order information, active information pick up, information-based control laws, prospective control, and direct learning. Examples are included to illustrate these concepts and to show how they can be applied to the construction of robots. Action is described as emergent and self-organized. It is argued that knowledge about perception, action, and learning as it occurs in living organisms may facilitate the construction of robots, more obviously so if the aim is to construct (to some extent) biologically plausible robots.
url https://doi.org/10.5772/55671
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