Optimization of 3D Coverage Layout for Multi-UAV Collaborative Lighting in Emergency Rescue Operations

In emergency rescue scenarios, Unmanned Aerial Vehicles (UAVs) play a pivotal role in navigating complex terrains and high-risk environments. This paper proposes an optimization model for the three-dimensional coverage layout of a multi-UAV collaborative lighting system, specifically designed to meet the spatial requirements of emergency operations. An enhanced Particle Swarm Optimization (PSO) algorithm is employed to tackle the layout challenges, featuring adaptive inertia weights and asymmetric learning factors to improve both efficiency and global search capabilities. The simulation results demonstrate that the proposed method significantly enhances coverage efficiency, achieving over 90% coverage in critical areas while ensuring precise UAV positioning. Additionally, the algorithm shows faster convergence and stronger global search ability, effectively optimizing UAV deployment and improving operational efficiency during rescue missions. This study offers a practical and reliable layout solution for multi-UAV collaborative lighting systems, which is crucial for reducing rescue times, ensuring operational safety, and improving resource allocation in emergency responses.

@article{Jiang2024,
  title     = {Optimization of 3D Coverage Layout for Multi-UAV Collaborative Lighting in Emergency Rescue Operations},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {10},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Dan Jiang and Rui Yan},
  doi       = {10.14569/IJACSA.2024.0151050},
  url       = {https://doi.org/10.14569/IJACSA.2024.0151050}
}