TY - JOUR T1 - SÜRÜ ROBOTLARI İÇİN İŞ BİRLİĞİNE DAYALI YOL PLANLAMA VE ENGELDEN KAÇINMA ALGORİTMALARININ KARŞILAŞTIRMALI ANALİZİ TT - A COMPARATIVE ANALYSIS OF COLLABORATIVE PATH PLANNING AND OBSTACLE AVOIDANCE ALGORITHMS FOR SWARM ROBOTS AU - Altındaş, Müsemma AU - Gökrem, Levent PY - 2025 DA - September Y2 - 2025 DO - 10.21923/jesd.1616072 JF - Mühendislik Bilimleri ve Tasarım Dergisi JO - MBTD PB - Süleyman Demirel Üniversitesi WT - DergiPark SN - 1308-6693 SP - 777 EP - 790 VL - 13 IS - 3 LA - tr AB - Bu çalışmada, sürü robotlarının koordineli hareketi için geliştirilen üç farklı yol planlama ve engelden kaçınma algoritması (VFH–Pure Pursuit, RRT–Pure Pursuit ve PRM–Pure Pursuit) karşılaştırmalı olarak analiz edilmiştir. Önerilen yöntemlerde her bir sürü robotunun bağımsız olarak çevresini algılaması, engellerden kaçınması ve belirlenen hedefe organize şekilde ulaşması hedeflenmiştir. Deneysel çalışmalar, 50x50 boyutlarında tanımlanmış üç farklı ortamda; 3, 5 ve 7 robot ile, ileriye bakma mesafesi (l_d) 0.5 olarak belirlenerek gerçekleştirilmiştir. VFH tabanlı yöntemde, robotlar çevresel koşullara anlık tepki verirken, RRT ve PRM tabanlı algoritmalarda başlangıç ve hedef konumlar arasında önceden planlanmış çarpışmasız yollar kullanılmıştır. Simülasyon sonuçları; robot sayısı arttıkça tamamlanma süresinin uzadığını, ancak PRM algoritmasının daha kısa mesafeli ve optimize yollar sunduğunu göstermiştir. Özellikle PRM–Pure Pursuit yöntemi, en düşük ortalama yol mesafesiyle en verimli performansı sergilemiştir. Elde edilen bulgular, sürü robotları için görev bazlı algoritma seçimlerinin başarımı doğrudan etkilediğini ve planlı yapıdaki algoritmaların karmaşık ortamlarda daha etkili sonuçlar verdiğini ortaya koymaktadır. KW - Engelden Kaçma KW - Mobil Robotlar KW - Sürü Robotiği KW - Yol Planlama KW - Yol Takip Etme. N2 - In this study, three different path planning and obstacle avoidance algorithms (VFH–Pure Pursuit, RRT–Pure Pursuit, and PRM–Pure Pursuit) developed for the coordinated movement of swarm robots are comparatively analyzed. The proposed methods aim for each swarm robot to independently perceive its environment, avoid obstacles, and reach a predefined target in an organized manner. Experimental studies were conducted in three different environments, each defined as 50x50 units in size, using 3, 5, and 7 robots, with a look-ahead distance (l_d) set to 0.5. In the VFH-based approach, robots react to environmental conditions in real time, while in RRT and PRM-based algorithms, pre-planned collision-free paths are used between start and goal positions. Simulation results demonstrate that as the number of robots increases, the completion time also increases; however, the PRM algorithm offers shorter and more optimized paths. 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