A Novel Target Searching Algorithm for Swarm UAVs Inspired From Spatial Distribution Patterns of Plant Population

Abstract

Like some social animal groups, the evolution of plant populations in nature also contains swarm intelligence. Aiming at the problem of swarm Unmanned Aerial Vehicles (UAVs) target searching in complex and unknown environments, this paper explores search models suitable for swarm UAVs by investigating the spatial distribution patterns of plant population and proposes a novel robot bean optimization algorithm (RBOA) based on Cauchy distribution and normal distribution (CRBOA). It has been demonstrated by comparative experiments with RBOA and adaptive robotic particle swarm optimization (A-RPSO) that the CRBOA has excellent stability, striking a good balance between exploration and exploitation.