Method and Software for Multi-Parametric Choosing Algorithms of UAVs Placement and Routing in Hazardous Space

Abstract

This paper considers the tasks of choosing algorithms for placing unmanned aerial vehicles (UAVs) to support communications and route formation in a hazardous cyber-physical 3D space. UAV placement is interpreted as the selection of spatial coordinates for relay UAVs that form a communication chain between a data source and receiver, primarily in flying LiFi or free-space optical networks. The proposed adaptive method selects a routing or placement algorithm using several environment indicators: obstacle density, obstacle-shape complexity, dynamic changes, communication constraints, cyber-physical risk, and mission priority. The method combines environment analysis, multi-indicator assessment of A*, RRT*, and greedy search, route construction, relay UAV placement, and swarm-characteristic evaluation. A software implementation in Python/Panda3D supports scenario configuration, adaptive algorithm selection, metric logging, and experimental comparison. The reported procedure is reproducible because input scenarios, seeds, algorithm modes, and run-level measurements are fixed. A series of 100 runs confirmed correct adaptive selection and no degradation of controlled safety and communication characteristics in the tested static scenarios.