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

Simulation enables robots to plan and estimate the outcomes of prospectiveactions without the need to physically execute them. We introduce aself-supervised learning framework to enable robots model and predict theirmorphology, kinematics and motor control using only brief raw video data,eliminating the need for extensive real-world data collection and kinematicpriors. By observing their own movements, akin to humans watching theirreflection in a mirror, robots learn an ability to simulate themselves andpredict their spatial motion for various tasks. Our results demonstrate thatthis self-learned simulation not only enables accurate motion planning but alsoallows the robot to detect abnormalities and recover from damage.

Teaching Robots to Build Simulations of Themselves