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 focuses on the problem of estimating bearing vectors between theagents in a two dimensional multi-agent network based on subtended anglemeasurements, called edge localization problem. We propose an edge localizationgraph to investigate the solvability of this problem and a distributedestimation method via orientation estimation of virtual agents to solve theproblem. Under the proposed method, the estimated bearing vector exponentiallyconverges to the real one with a common bias if and only if the edgelocalization graph has an oriented spanning tree. Furthermore, the estimatedvariables exponentially converge to the true values if the edge localizationgraph has an oriented spanning tree with a root knowing the bearing vector fromit to one of its neighbors.

Edge Localization in Two Dimensional Space via Orientation Estimation