Path planning based on unmanned aerial vehicle performance with segmented cellular genetic algorithm

Yıl 2025, Cilt: 40 Sayı: 1, 135 - 154, 16.08.2024

Ahmet Gezer , Onder Turan , Tolga Baklacıoğlu

https://doi.org/10.17341/gazimmfd.1156817

Öz

Unmanned Aerial Vehicles (UAV) have a wide range of use on industrial, military and commercial areas. Comprehensive and error-free sub-systems are needed to provide planning, management and coordination of UAVs which are designed for variable purposes with different capabilities and sizes. An important part of UAV technological development consists of improvements in the scope of path planning. Different choices can be made in path planning according to operational priorities, it may be preferred to reach the destination as fast as possible or to increase the airtime by compromising speed. Fuel data of cruise, climb and descent phases are used in the path planning algorithm for every speed and altitude that the UAV can fly. Thus, economical and airtime-maximizing paths could be produced on the basis of performance characteristics compatible with the kinematic constraints customized for the UAV. In this thesis, Cellular (cGA) and Segmented Cellular Genetic Algorithm (scGA) are proposed. The novel overprotective algorithm which has a fixed initial population and segmented chromosome structure achieves a high convergence speed to optimal solution and can generate paths which have 5.2 times higher fitness value on average compared with a conventional Genetic Algorithm (GA). It has been observed that scGA improves the initial population in terms of the best solutions 1.9 times and the general population 5.8 times better compared with GA.

Anahtar Kelimeler

Path Planning, Trajectory Planning, Genetic Algorithm, Evolutionary Algorithm, UAV, Aircraft Performance

Parçalı hücresel genetik algoritma ile insansız hava aracı performansına dayalı yol planlama

Öz

İnsansız Hava Araçları (İHA), endüstriyel, askerî ve ticari geniş bir uygulama alanına sahiptir. Değişken amaçlar için tasarlanmış farklı yeteneklere ve boyutlara sahip İHA’ların; planlama, yönetme ve koordinasyonunu sağlayabilmek için hatasız çalışan kapsamlı alt sistemlere ihtiyaç vardır. İHA teknolojik gelişiminin önemli bir parçası, yol planlama alanındaki iyileştirmelerden oluşmaktadır. Yol planlamada operasyonel önceliklere göre farklı tercihler yapılabilir, varış noktasına en hızlı şekilde ulaşılması veya hızdan ödün vererek havada kalma süresinin uzatılması istenebilir. Bir İHA’ya ait uçabildiği her hız ve her irtifa için; seyir, tırmanma ve alçalma fazlarına ait yakıt verileri yol planlama algoritmasında kullanılmıştır. Böylece, bir İHA için özelleştirilmiş kinematik kısıtlara uyumlu performans özellikleri temelinde ekonomik ve havada kalma süresini uzatan yollar üretilebilmiştir. Bu tez çalışmasında, Hücresel (cGA) ve Parçalı Hücresel Genetik Algoritma (scGA) önerilmiştir. Sabit başlangıç popülasyonu ve parçalı kromozom yapısına sahip aşırı korumacı yeni algoritma; optimal çözüme yüksek yakınsama hızı elde etmiş, geleneksel bir genetik algoritmaya (GA) kıyasla ortalama 5,2 kat daha yüksek uygunluk değerine sahip yollar üretebilmiştir. scGA’nın GA’ya kıyasla, başlangıç popülasyonuna göre en iyi çözümü 1,9 kat ve genel popülasyonu 5,8 kat daha iyi geliştirdiği gözlenmiştir.

Anahtar Kelimeler

Yol Planlama, Yörünge Planlama, Genetik Algoritma, Evrimsel Algoritma, İHA, Hava Aracı Performansı

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