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 heuristic enables each UAV to find an optimal path that minimizes the detection time of defects in pipe networks while avoiding collisions with obs...

وصف كامل

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Aljalaud, Faten, Kurdi, Heba, Youcef-Toumi, Kamal
مؤلفون آخرون: Massachusetts Institute of Technology. Department of Mechanical Engineering
التنسيق: مقال
منشور في: Multidisciplinary Digital Publishing Institute 2023
الوصول للمادة أونلاين:https://hdl.handle.net/1721.1/150669
الوصف
الملخص:This paper presents a novel path planning heuristic for multi-UAV pipe inspection missions inspired by the booby bird’s foraging behavior. The heuristic enables each UAV to find an optimal path that minimizes the detection time of defects in pipe networks while avoiding collisions with obstacles and other UAVs. The proposed method is compared with four existing path planning algorithms adapted for multi-UAV scenarios: ant colony optimization (ACO), particle swarm optimization (PSO), opportunistic coordination, and random schemes. The results show that the booby heuristic outperforms the other algorithms in terms of mean detection time and computational efficiency under different settings of defect complexity and number of UAVs.