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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

With increasing numbers of mobile robots arriving in real-world applications,more robots coexist in the same space, interact, and possibly collaborate.Methods to provide such systems with system size scalability are known, forexample, from swarm robotics. Example strategies are self-organizing behavior,a strict decentralized approach, and limiting the robot-robot communication.Despite applying such strategies, any multi-robot system breaks above a certaincritical system size (i.e., number of robots) as too many robots share aresource (e.g., space, communication channel). We provide additional evidencebased on simulations, that at these critical system sizes, the systemperformance separates into two phases: nearly optimal and minimal performance.We speculate that in real-world applications that are configured for optimalsystem size, the supposedly high-performing system may actually live onborrowed time as it is on a transient to breakdown. We provide two modelingoptions (based on queueing theory and a population model) that may help tosupport this reasoning.

Do We Run Large-scale Multi-Robot Systems on the Edge? More Evidence for Two-Phase Performance in System Size Scaling