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

Given a set of robots with arbitrary initial location and no agreement on aglobal coordinate system, convergence requires that all robots asymptoticallyapproach the exact same, but unknown beforehand, location. Robots areoblivious-- they do not recall the past computations -- and are allowed to movein a one-dimensional space. Additionally, robots cannot communicate directly,instead they obtain system related information only via visual sensors. We drawa connection between the convergence problem in robot networks, and thedistributed \emph{approximate agreement} problem (that requires correctprocesses to decide, for some constant $\epsilon$, values distance $\epsilon$apart and within the range of initial proposed values). Surprisingly, eventhough specifications are similar, the convergence implementation in robotnetworks requires specific assumptions about synchrony and Byzantineresilience. In more details, we prove necessary and sufficient conditions forthe convergence of mobile robots despite a subset of them being Byzantine (i.e.they can exhibit arbitrary behavior). Additionally, we propose a deterministicconvergence algorithm for robot networks and analyze its correctness andcomplexity in various synchrony settings. The proposed algorithm tolerates fByzantine robots for (2f+1)-sized robot networks in fully synchronous networks,(3f+1)-sized in semi-synchronous networks. These bounds are optimal for theclass of cautious algorithms, which guarantee that correct robots always moveinside the range of positions of the correct robots.

Optimal byzantine resilient convergence in oblivious robot networks