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

This paper proposes a new approach to achieve direct visual servoing (DVS)based on discrete orthogonal moments (DOMs). DVS is performed in such a waythat the extraction of geometric primitives, matching, and tracking steps inthe conventional feature-based visual servoing pipeline can be bypassed.Although DVS enables highly precise positioning, it suffers from a limitedconvergence domain and poor robustness due to the extreme nonlinearity of thecost function to be minimized and the presence of redundant data between visualfeatures. To tackle these issues, we propose a generic and augmented frameworkthat considers DOMs as visual features. By using the Tchebichef, Krawtchouk,and Hahn moments as examples, we not only present the strategies for adaptivelytuning the parameters and order of the visual features but also exhibit ananalytical formulation of the associated interaction matrix. Simulationsdemonstrate the robustness and accuracy of our approach, as well as itsadvantages over the state-of-the-art. Real-world experiments have also beenperformed to validate the effectiveness of our approach.

Direct Visual Servoing Based on Discrete Orthogonal Moments