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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Humans and animals excel in combining information from multiple sensorymodalities, controlling their complex bodies, adapting to growth, failures, orusing tools. These capabilities are also highly desirable in robots. They aredisplayed by machines to some extent - yet, as is so often the case, theartificial creatures are lagging behind. The key foundation is an internalrepresentation of the body that the agent - human, animal, or robot - hasdeveloped. In the biological realm, evidence has been accumulated by diversedisciplines giving rise to the concepts of body image, body schema, and others.In robotics, a model of the robot is an indispensable component that enables tocontrol the machine. In this article I compare the character of bodyrepresentations in biology with their robotic counterparts and relate that tothe differences in performance that we observe. I put forth a number of axesregarding the nature of such body models: fixed vs. plastic, amodal vs. modal,explicit vs. implicit, serial vs. parallel, modular vs. holistic, andcentralized vs. distributed. An interesting trend emerges: on many of the axes,there is a sequence from robot body models, over body image, body schema, tothe body representation in lower animals like the octopus. In some sense,robots have a lot in common with Ian Waterman - "the man who lost his body" -in that they rely on an explicit, veridical body model (body image taken to theextreme) and lack any implicit, multimodal representation (like the bodyschema) of their bodies. I will then detail how robots can inform thebiological sciences dealing with body representations and finally, I will studywhich of the features of the "body in the brain" should be transferred torobots, giving rise to more adaptive and resilient, self-calibrating machines.

Body models in humans, animals, and robots: mechanisms and plasticity