Mobil Robotların Yol Planlamasında Doğrusallığın İncelenmesi

Abstract

Endüstriyel ortamlarda giderek daha fazla kullanılan mobil robotlar için yol planlanması önemli bir problemdir. Bu problem, engelli bir ortamda başlangıç düğümünden hedef düğüme kadar mesafe ve süre gibi bazı kriterler dikkate alınarak engellere çarpmadan uygun bir yolun bulunmasıdır. Alternatif yolların üretilmesinde doğrusal (düz çizgi) veya doğrusal olmayan (eğri) amaç fonksiyonlarının kullanılması performansı önemli ölçüde etkilemektedir. Bu çalışmada, küresel yol planlama için farklı zorluk derecelerine sahip ortamlarda doğrusal ve doğrusal olmayan amaç fonksiyonlarının kullanımı karşılaştırmalı incelenmiştir. Uygun yolların bulunmasında evrimsel algoritmalardan biri olan genetik algoritma (Genetic Algorithm, GA) kullanılmıştır. Simülasyon sonuçları, mobil robotların yol planlamasında doğrusal amaç fonksiyonu kullanılmasının hem mesafe hem de algoritma çalışma süresi açısından avantajlı olduğunu göstermiştir.

Keywords

• Mobil Robot
• Yol Planlama
• Optimizasyon
• Genetik Algoritma
• Yol Doğrusallığı

Investigation of Linearity in Path Planning of Mobile Robot

Abstract

Path planning is an important problem for mobile robots, which are increasingly used in industrial environments. This problem is to find a suitable path from a starting node to a target node without colliding obstacles, taking into account some criteria such as distance and time. The use of linear (straight line) or nonlinear (curve) objective functions in the generation of alternative paths significantly affects the performance. In this study, the use of linear and nonlinear objective functions for global path planning in environments with different degrees of difficulty has been comparatively examined. Genetic algorithm (GA), one of the evolutionary algorithms, was used to find suitable paths. The simulation results showed that using the linear objective function in path planning of mobile robots is advantageous in terms of both distance and algorithm running time.

Keywords

• Mobile Robot
• Path Planning
• Optimization
• Genetic Algorithm
• Path Linearity

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