English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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

On the Ecological Approach to Information and Control for Roboticists