MOBİL ROBOTLAR İÇİN YAPAY POTANSİYEL ALAN TABANLI YOL PLANLAMA ALGORİTMALARININ ORTAK SORUNLARINA ETKİLİ ÇÖZÜMLER
Otonom Yol Planlaması (OYP) yeteneği bir mobil robotun otonom seviyesini belirleyen başlıca faktörlerden birisidir. Literatürde her ne kadar faklı yöntemler otonom yol planlaması için kullanılıyor olsa dahi, Yapay Potansiyel Alanlara (YPA) dayalı yol planlaması yaklaşımı modelleme kolaylığı ve hesaplama performansı ile oldukça yaygın bir kullanım alanına sahiptir. Grid tabanlı bir yol planlaması yaklaşımı olan YPA tabanlı OYP, genellikle çok sayıda temel hareketi modelleyen itici ve çekici yönde bileşenin belirli bir denklem ile bir araya getirilmesi ve bu potansiyel alanın gradientinin hesaplanarak vektör alanın elde edilmesi ile gerçekleştirilir. Bu çalışma kapsamında YPA tabanlı OYP amacıyla kullanılan temel modeller incelenmiş, nasıl gerçekleştirildiğiklerine değinilmiş ve bileşke potansiyel alanın nasıl üretildiğinden bahsedilmiştir. Her ne kadar YPA tabanlı OYP yaklaşımlarının avantajları olsa dahi yerel minimum, çok yakın konumlandırılmış engeller, osilasyon ve engellere çok yakın konumlandırılmış hedef gibi problemleri de vardır. Çalışma kapsamında bu problemlerin teker teker tanımlamaları yapılmış ve literatürde bu problemlerin çözümü için önerilen yaklaşımlara detaylı olarak değinilmiştir. Sonuç olarak etkin bir YPA tabanlı OYP çözümü elde etmek için kıvrımsız vektör alanı üretilmesi, temel potansiyel alanların üssel fonksiyonlar ile sınırlandırılması, sanal potansiyel alanların kullanılması ve harmonik fonksiyonlar ile modellemelerin gerçekleştirilmesi gerektiği görülmüştür.
EFFECTIVE SOLUTIONS FOR COMMON PROBLEMS OF ARTIFICIAL POTENTIAL FIELD BASED PATH PLANNING ALGORITHMS FOR MOBILE ROBOTS
Abstract
Autonomous Path Planning (APP) capability is one of the main factors determining the autonomous level of a mobile robot. Although different methods are used for APP in the literature, the path planning approach based on Artificial Potential Fields (APF) has a very common usage area with its modeling ease and computational performance. APF-based APP, which is a grid-based path planning approach, is usually performed by combining a repulsive and attractive component that models many basic motions with a certain equation and calculating the gradient of this potential field to obtain the vector field. In this study, the basic models used for APF-based APP are examined, and how they are realized and how the resultant potential field is produced are mentioned. Although APF-based APP approaches have advantages, they also have problems such as local minimum, obstacles positioned too close, oscillation, and targets positioned too close to obstacles. Within the scope of the study, these problems were defined one by one and the approaches suggested in the literature for the solution of these problems were mentioned in detail. As a result, it has been seen that to obtain an effective APF-based APP solution, it is necessary to generate a convolutional vector field, limit the fundamental potential fields with exponential functions, use virtual potential fields and perform models with harmonic functions.
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