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

Very distinct strategies can be deployed to recognize and characterize anunknown environment or a shape. A recent and promising approach, especially inrobotics, is to reduce the complexity of the exploratory units to a minimum.Here, we show that this frugal strategy can be taken to the extreme byexploiting the power of statistical geometry and introducing new invariantfeatures. We show that an elementary robot devoid of any orientation orobservation system, exploring randomly, can access global information about anenvironment such as the values of the explored area and perimeter. The exploredshapes are of arbitrary geometry and may even non-connected. From a dictionary,this most simple robot can thus identify various shapes such as famousmonuments and even read a text.

Frugal random exploration strategy for shape recognition using statistical geometry