Adaptive Particle Swarm Optimization for through-foliage target detection with drone swarms
Systems and Control
2023-10-17 v1 Neural and Evolutionary Computing
Systems and Control
Abstract
This work contributes to efforts on autonomously detecting a vegetation-occluded target by airborne observers. It investigates and enhances previous work on a Particle Swarm Optimization (PSO) strategy for Airborne Optical Sectioning (AOS) drone swarms. First, it identifies two issues with that method and proposes to resolve them by a leader stabilization for its scattering and projection-based line positions for its default scanning pattern. Second, it connects this method to other PSO variants and presents a new adaptive PSO strategy for AOS drone swarms that draws on the ideas of Adaptive PSO (APSO).
Keywords
Cite
@article{arxiv.2310.10320,
title = {Adaptive Particle Swarm Optimization for through-foliage target detection with drone swarms},
author = {Julia Pöschl},
journal= {arXiv preprint arXiv:2310.10320},
year = {2023}
}