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

We propose a novel iterative approach for crossing the reality gap thatutilises live robot rollouts and differentiable physics. Our method,RealityGrad, demonstrates for the first time, an efficient sim2real transfer incombination with a real2sim model optimisation for closing the reality gap.Differentiable physics has become an alluring alternative to classicalrigid-body simulation due to the current culmination of automaticdifferentiation libraries, compute and non-linear optimisation libraries. Ourmethod builds on this progress and employs differentiable physics for efficienttrajectory optimisation. We demonstrate RealitGrad on a dynamic control taskfor a serial link robot manipulator and present results that show itsefficiency and ability to quickly improve not just the robot's performance inreal world tasks but also enhance the simulation model for future tasks. Oneiteration of RealityGrad takes less than 22 minutes on a desktop computer whilereducing the error by 2/3, making it efficient compared to other sim2realmethods in both compute and time. Our methodology and application ofdifferentiable physics establishes a promising approach for crossing thereality gap and has great potential for scaling to complex environments.

Follow the Gradient: Crossing the Reality Gap using Differentiable Physics (RealityGrad)