Autonomous Multi-UAV Path Planning in Pipe Inspection Missions Based on Booby Behavior

This paper presents a novel path planning heuristic for multi-UAV pipe inspection missions inspired by the booby bird’s foraging behavior. The enables each UAV to find an optimal that minimizes detection time of defects in networks while avoiding collisions with obstacles and other UAVs. proposed method is compared four existing algorithms adapted scenarios: ant colony optimization (ACO), particle swarm (PSO), opportunistic coordination, random schemes. results show outperforms terms mean computational efficiency under different settings defect complexity number