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

Unmanned aerial vehicles (UAVs) are being employed in many areas such asphotography, emergency, entertainment, defence, agriculture, forestry, miningand construction. Over the last decade, UAV technology has found applicationsin numerous construction project phases, ranging from site mapping, progressmonitoring, building inspection, damage assessments, and material delivery.While extensive studies have been conducted on the advantages of UAVs forvarious construction-related processes, studies on UAV collaboration to improvethe task capacity and efficiency are still scarce. This paper proposes a newcooperative path planning algorithm for multiple UAVs based on the stag huntgame and particle swarm optimization (PSO). First, a cost function for each UAVis defined, incorporating multiple objectives and constraints. The UAV gameframework is then developed to formulate the multi-UAV path planning into theproblem of finding payoff-dominant equilibrium. Next, a PSO-based algorithm isproposed to obtain optimal paths for the UAVs. Simulation results for a largeconstruction site inspected by three UAVs indicate the effectiveness of theproposed algorithm in generating feasible and efficient flight paths for UAVformation during the inspection task.

Stag hunt game-based approach for cooperative UAVs