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

Learning schemes for planning and control are limited by the difficulty ofcollecting large amounts of experimental data or having to rely onhigh-fidelity simulations. This paper explores the potential of a proposedlearning scheme that leverages dimensionless numbers based on Buckingham's$\pi$ theorem to improve data efficiency and facilitate knowledge sharingbetween similar systems. A case study using car-like robots comparestraditional and dimensionless learning models on simulated and experimentaldata to validate the benefits of the new dimensionless learning approach.Preliminary results show that this new dimensionless approach could acceleratethe learning rate and improve the accuracy of the model and should beinvestigated further.

Using Buckingham's $\pi$ Theorem for Multi-System Learning Transfer: a Case-study with 3 Vehicles Sharing a Database