Browsing by Author "Korkmaz, Mehmet"

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Citation - WoS: 2
Citation - Scopus: 2
Autonomously Simultaneous Localization and Mapping Based on Line Tracking in a Factory-Like Environment
(VSB-TECHNICAL UNIV OSTRAVA, 2019) Durdu, Akif; Korkmaz, Mehmet
This study is related to SLAM, also known simultaneous localization and mapping which is highly important and an indispensable issue for autonomous mobile robots. Both an environment mapping and an agent's localization are provided with SLAM systems. However, while performing SLAM for an unknown environment, the robot is navigated by three different ways: a user guidance, random movements on an exploration mode or exploration algorithms. A user guidance or random exploration methods have some drawbacks that a user may not be able to observe the agent or random process may take a long time. In order to answer these problems, it is searched for a new and autonomous exploration algorithm for SLAM systems. In this manner, a new kind of left-orientated autonomous exploration algorithm for SLAM systems has been improved. To show the algorithm effectiveness, a factorylike environment is made up on the ROS (Robot Operating System) platform and navigation of the agent is observed. The result of the study demonstrates that it is possible to perform SLAM autonomously in any similar environment without the need of the user interference.
A Deep Learning-Based Quality Control Application
(2020) Korkmaz, Mehmet; Barstugan, Mücahid
The study at hand is an implementation of a deep learning strategy on a quality control scheme. The quality control process is a substantial part of product manufacturing. It fundamentally targets to detect and eliminate defective products so that the erroneous ones will not be delivered to the customers. Final product control has been usually performed by experts. Generally, those experts can easily distinguish defective and trouble-free products. On the other hand, growing product lines and human-based natural problems may affect the efficiency of that quality control process. Therefore, there is an increasing demand for computer-aided software that will take the place of those experts. This software or algorithm typically increases the product control rate. Besides, they make it possible to avoid from human-driven faults. The algorithms run at high speed and efficacy under conditional situations i.e. perfectly lightening environment. However, they may easily fail when small changes occur in the environment or the product for some duties that humans can easily achieve. These robustness problems make them not preferable, although they have numerous advantages. At this point, deep learning-based artificial intelligence algorithms have made a significant enhancement. The general development and achievable prices of GPUs pave the way for using numerous training examples so that better networks, meaning more robust, can be created for the applications. To this end, we carried on an experiment that could realize the deep learning strategy on the quality control scheme. For this purpose, the developed algorithms applied to the inverters conveying on a product line to confirm whether they are erroneous or not. Results show that developed strategy could detect defective products similar to the human being.
Citation - WoS: 10
Citation - Scopus: 12
A Novel Map-Merging Technique for Occupancy Grid-Based Maps Using Multiple Robots: a Semantic Approach
(2019) Durdu, Akif; Korkmaz, Mehmet
Map merging is a noteworthy phenomenon for cases such as search and rescue and disaster areas in which the duration is quite significant when gathering information about an environment. It is obvious that the total mapping time decreases if the number of agents (robots) increases. However, the use of multiple agents leads to problems such as task allocation schemes and the fusing of local maps. Examining the present methods, it is generally observed that the common features of local maps have been found and the global map is formed by obtaining related transformation between local maps. However, such implementations may be risky when local maps have symmetrical areas. Hence, a novel and semantic approach has been developed to solve this problem. The developed method counts on the reliability level of feature points. If relevant feature points are trusted, local maps are merged according to the best point or points. The simulation results from a robot operating system and a real-time experiment support the proposed method’s efficiency, and mapping can be performed even for environments that have symmetrical similar parts and the task time can thus be reduced.
Citation - WoS: 4
Citation - Scopus: 10
Optimal Design of a Variable Coefficient Fractional Order Pid Controller by Using Heuristic Optimization Algorithms
(SCIENCE & INFORMATION SAI ORGANIZATION LTD, 2019) Aydoğdu, Ömer; Korkmaz, Mehmet
This paper deals with an optimal design of a new type Variable coefficient Fractional Order PM (V-FOPID) controller by using heuristic optimization algorithms. Although many studies have mainly paid attention to correct the performance of the system's transient and steady state responses together, few studies are interested in both transient and steady state performances separately. It is obvious that handling these two cases independently will bring out a better control response. However, there are no studies using different controller parameters for the transient and steady state responses of the system in fractional order control systems. The major contribution of the paper is to fill this gap by presenting a novel approach. To justify the claimed efficiency of the proposed V-FOPID controller, variable coefficient controllers and classical ones are tested through a set of simulations which is about controlling of an Automatic Voltage Regulator (AVR) system. According to the obtained results, first of all it was observed that proposed V-FOPID controller has superiority to the classical PID, Variable coefficient PID (V-PID) and classical Fractional Order PID (FOPID) controllers. Secondly, Particle Swarm Optimization (PSO) algorithm has shown its advantage compared to the Artificial Immune System (AIS) algorithm for the controller design.
Slam ve Vslam Algoritmalarının İncelenmesi, Yeni Bir Çoklu Robot Harita Birleştirme Yönteminin Geliştirilmesi ve Uygulanması
(Konya Teknik Üniversitesi, 2019) Korkmaz, Mehmet; Durdu, Akif
Eş zamanlı konumlama ve haritalama (SLAM) probleminin çözümü günümüz teknolojisinde de kullanılan birçok ileri araştırmanın temellerini oluşturmuştur. Bu tez çalışmasında konunun önemine binaen klasik ve modern dönem SLAM algoritmalarının her ikisine dair incelemeler yapılmıştır. Klasik dönem SLAM algoritmaları için mevcut algoritmalar ve sensörlerin karşılaştırıldığı farklı uygulamalar yapılmıştır. Modern dönem SLAM yaklaşımları için mevcut yöntemlerin irdelendiği çalışmalara ek olarak ORB-SLAM yönteminin çıktılarının yoğunluk tabanlı haritalara dönüştürülmesi üzerine bir geliştirme yapılmış ve bir uygulama ile sonuçlar gösterilmiştir. Bunlara ek olarak SLAM problemi komşuluğunda incelenen aktif SLAM ve harita birleştirme konuları üzerine de çalışmalar yapılmıştır. Aktif SLAM algoritmaları navigasyon kısmı için farklı iki yeni yaklaşım önerilmiştir. Çalışmanın birisinde derin öğrenme tabanlı bir metot geliştirilmiş diğerinde ise sola yönelimli olarak adlandırılan bir algoritma taslağı üzerinde durulmuştur. Geliştirilen algoritmalar bilgisayar benzetimi ve gerçek zamanlı robotlar üzerinde denenerek sonuç başarımları gösterilmiştir. Çoklu robot uygulamaları yerel haritaların birleştirilmesi problemi için mevcut yöntemlerin simetrik ortam özelliklerinin bulunduğu durumlarda başarımlarının iyi olmadığı görülmüştür. Bu eksiklik baz alınarak tez kapsamında güvenilir özellik tanımı ve buna bağlı anlamlı harita birleştirme algoritması fikri önerilmiştir. Bu yeni yöntem, bilgisayar benzetimi ve gerçek zamanlı uygulamalarla denenmiş ve mevcut özellik tabanlı birleştirme yöntemlerine göre üstünlükleri gösterilmiştir. Bunlara ilave olarak robot dışında insanlar üzerinde konumlama/haritalama uygulamalarının nasıl olacağı irdelenmiştir. İnsan ayağına monte edilen bir içsel ölçüm birimi (IMU) ile gerçek zamanlı denemeler yapılmış ve başlangıç noktası bilinmeyen durumlarda konumlama ve başlangıç noktasının nasıl bulunacağına dair durumlar incelenmiştir.