On the Ecological Approach to Information and Control for Roboticists
Author(s) -
Jorge Ibáñez-Gijón,
Alex Díaz,
Lorena Lobo,
David M. Jacobs
Publication year - 2013
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/55671
Subject(s) - computer science , robot , action (physics) , construct (python library) , perception , control (management) , artificial intelligence , robotics , human–computer interaction , active perception , action selection , order (exchange) , cognitive science , ecology , knowledge management , epistemology , psychology , business , philosophy , physics , finance , quantum mechanics , biology , programming language
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, informationbased 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.This material is based upon work supported by grant FFI2009‐13416‐C02‐02 of the Spanish Ministry of Science and Innovation
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