Yazar "Eren, Tolga" seçeneğine göre listele

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    3-cycle-free persistence for cooperative control of formations with acyclic control structure ?
    (2009) Eren, Tolga
    In this paper, we analyze the problem of acquiring 3-cycle-free persistent formations of mobile autonomous agents that have acyclic control structure. Nyquist-like criterion for formation stabilization is used in literature for the problem of relative formation stabilization. For this purpose, spectral properties of the Laplacian matrix are used in evaluating desirable structural properties of formations. Establishing measures of near-periodicity are useful in quantifying formation stability margins. In this paper, we analyze constructions to create non-3-periodic persistent formations, i.e., we study the constructions to create 3-cycle-free persistent formations. Central to the development of our analysis will be the use of tools from rigidity theory and graph Laplacians.
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    3-Cycle-Free Rigidity for Multi-Agent Control Systems
    (Ieee, 2009) Eren, Tolga
    This paper is concerned with rigid formations of mobile autonomous agents. For the problem of relative formation stabilization, Nyquist-like criterion for formation stabilization is used in literature, where spectral properties of the Laplacian matrix play a role in evaluating desirable structural properties of formations. Establishing measures of near-periodicity would be useful in quantifying formation stability margins. In this paper, we analyze constructions to create non-3-periodic rigid formations, i.e., we study the constructions to create 3-cycle-free rigid formations. Central to the development of our analysis will be the use of tools from rigidity theory and graph Laplacians.
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    Combinatorial measures of rigidity in wireless sensor and robot networks
    (Ieee, 2015) Eren, Tolga
    This paper presents a combinatorial rigidity approach to measure rigidity and redundant rigidity for wireless sensor and robot networks. Redundant rigidity is a necessary condition for global rigidity, which is desirable for network localization. Redundant rigidity also provides rigidity robustness in formation control and network localization against structural changes, such as link losses. In 2-space, Laman's Theorem provides us a test to determine whether there are at least 2n - 3 well-distributed edges, which are independent edges. However, we need more than the requirements in Laman's theorem to know whether "all the edges" are well-distributed, including redundant edges. In 3-space, there is no known combinatorial test for rigidity. However, we can still provide a generic redundancy measure. In this work, we evaluate the distribution of redundant edges in 2-space and we examine the challenges to provide a measure of redundancy in 3-space.
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    Comparison of Particle Swarm Optimization, Bat Algorithm, Differential Evolution Algorithm and Firefly Algorithm Methods in Localization of Wireless Sensor Networks
    (Kırıkkale Üniversitesi, 2020) Doğru, Ahmet Sami; Eren, Tolga
    Positioning in wireless sensor networks is becoming an important issue in many areas every day. It is very important to find the location of the sensors quickly and with low error rate in applications such as military applications, emergency assistance, geographic tracking. In wireless sensor networks (WSN), location detection is cited as a multidimensional optimization problem. The efficiency of optimization methods varies according to the complexity of WSN’s. In this article, Particle Swarm Optimization (PSO), Bat Algorithm (BA), Differential Evolution Algorithm (DEA) and Firefly Algorithm (FA) methods were compared with the goal of solving the positioning problem in WSN. The proposed methods are optimization methods that are inspired by the characteristics of living beings in nature. In this study, heuristic optimization methods PSO, BA, DEA and FA were applied to a sample node distribution in Matlab environment and the results were observed.
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    Cooperative localization in wireless ad hoc and sensor networks using hybrid distance and bearing (angle of arrival) measurements
    (Springer, 2011) Eren, Tolga
    This article provides the graphical properties which can ensure unique localizability in cooperative networks with hybrid distance and bearing (angle of arrival) measurements. Furthermore, within the networks satisfying these graphical properties, this article identifies further sets of conditions so that the associated computational complexity becomes linear in the number of sensor nodes. We show how, by forming a spanning tree used once for distances and a second time for bearings where the underlying graph is connected, the localization problem can be made solvable in linear time with significantly less number of sensing links and smaller sensing radii of nodes compared with the cooperative networks with distance-only or bearing-only measurements. These easily localizable networks can be localized in polynomial time when measurements are noisy.
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    Direction problem in leader-follower formations of unmanned aerial vehicles and satellite clusters
    (2007) Eren, Tolga
    This paper is concerned with information structures used in rigid formations of unmanned aerial vehicles (UAV‘s) and micro-satellite clusters that have leader-follower architecture. The focus of the paper is on sensor/network topologies to secure control of rigidity. Specifically, we study the problem of determining the directions of links of an undirected formation so that the resulting formation is rigid, which is called the “Direction Problem.“ The algorithm given in the paper establishes a sequential way of determining the directions of links in a leader-follower formation from a given undirected rigid formation. The algorithm is related to our simpler process of finding two spanning trees, as well as the counts in Laman‘s Theorem. In common with tree finding algorithms, it is greedy, so the order of testing edges does not effect the size of maximal independent sets found, or the distribution of the edges through the UAV‘s and micro-satellites.
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    DKablosuz Sensör Ağlarında Konum Belirlemede Parçacık Sürü Optimizasyonu ve Yarasa Algoritması Yöntemlerinin Karşılaştırılması
    (2019) Doğru, Ahmet Sami; Temel, Uğur Burak; Eren, Tolga
    Kablosuz sensör ağlarında konum belirleme birçok uygulamada her geçen gün önemli bir konu haline gelmektedir. Aramakurtarma, doğal afet, coğrafi izleme ve takip gibi uygulamalarda sensörlerin konumunu doğru ve hızlı bir şekilde tespit etmekçok önemlidir. Kablosuz sensör ağlarında (KSA), konum belirleme çok boyutlu bir optimizasyon problemi olarak ifadeedilmektedir. KSA’ların karmaşıklığına göre optimizasyon yöntemlerinin performansları da değişmektedir. Bu çalışmada,Parçacık Sürü Optimizasyonu (PSO) ve Yarasa Algoritması (YA) metotları KSA’larda konum belirleme probleminin çözülmesiamacı ile karşılaştırılmıştır. Önerilen yöntemler, doğada yaşayan varlıkların hareketinden esinlenerek geliştirilmiş optimizasyonyöntemleridir. Bu çalışmada sezgisel optimizasyon metotlarından olan PSO ve YA, Matlab ortamında test sistemine uygulanmışolup sonuçlar değerlendirilmiştir.
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    The effects of random geometric graph structure and clustering on localizability of sensor networks
    (Sage Publications Inc, 2017) Eren, Tolga
    Graph rigidity provides the conditions of unique localizability for cooperative localization of wireless ad hoc and sensor networks. Specifically, redundant rigidity and 3-connectivity are necessary and sufficient conditions for unique localizability of generic configurations. In this article, we introduce a graph invariant for 3-connectivity, called 3-connectivity index. Using this index along with the rigidity and redundancy indices provided in previous work, we explore the rigidity and connectivity properties of two classes of graphs, namely, random geometric graphs and clustered graphs. We have found out that, in random geometric graphs and clustered graphs, it needs significantly less effort to achieve 3-connectivity once we obtain redundant rigidity. In reconsidering the general conditions for unique localizability, the most striking finding in random geometric graphs is that it is unlikely to observe a graph, in which 3-connectivity is satisfied before the graph becomes redundantly rigid. Therefore, in random geometric graphs, it is more likely sufficient to test only 3-connectivity for unique localizability. On the contrary to random geometric graphs, our findings indicate that 3-connectivity may be satisfied before the graph becomes redundantly rigid in clustered graphs, which means that, in clustered graphs, we have to test both redundant rigidity and 3-connectivity for unique localizability.
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    Formation shape control based on bearing rigidity
    (Taylor & Francis Ltd, 2012) Eren, Tolga
    Distance measurements are not the only geometric quantities that can be used for multi-agent formation shape control. Bearing measurements can be used in conjunction with distances. This article employs bearing rigidity for mobile formations, which was developed for robot and sensor network localisation, so that bearings can be used for shape control in mobile formations. The first part of this article examines graph theoretical models for formation network analysis and control law design that are needed to maintain the shape of a formation in two-dimensional space, while the formation moves as a cohesive whole. Bearing-based shape control for a formation of mobile agents involves the design of distributed control laws that ensure the formation moves, so that bearing constraints maintain some desired values. The second part of this article focuses on the design of a distributed control scheme for nonholonomic agents to solve the bearing-based formation shape control problem. In particular, a control law using feedback linearisation is proposed based on shape variables. We simulate the shape control behaviour on differential drive agents for an exemplary bearing rigid formation using the results obtained in the first and second parts of this article.
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    Graph invariants for unique localizability in cooperative localization of wireless sensor networks: Rigidity index and redundancy index
    (Elsevier Science Bv, 2016) Eren, Tolga
    Rigidity theory enables us to specify the conditions of unique localizability in the cooperative localization problem of wireless sensor networks: This paper presents a combinatorial rigidity approach to measure (i) generic rigidity and (ii) generalized redundant rigidity properties of graph structures through graph invariants for the localization problem in wireless sensor networks. We define the rigidity index as a graph invariant based on independent set of edges. It has a value between 0 and 1, and it indicates how close we are to rigidity. Redundant rigidity is required for global rigidity, which is associated with unique realization of graphs. Moreover, redundant rigidity also provides rigidity robustness in networked systems against structural changes, such as link losses. Here, we give a broader definition of redundant edge that we call the "generalized redundant edge." This definition of redundancy is valid for both rigid and non-rigid graphs. Next, we define the redundancy index as a graph invariant based on generalized redundant edges. It also has a value between 0 and 1, and it indicates the percentage of redundancy in a graph. These two indices allow us to explore the transition from non-rigidity to rigidity and the transition from rigidity to redundant rigidity. Examples on graphs are provided to demonstrate this approach. From a sensor network point of view, these two indices enable us to evaluate the effects of sensing radii of sensors on the rigidity properties of networks, which in turn, allow us to examine the localizability of sensor networks. We evaluate the required changes in sensing radii for localizability by means of the rigidity index and the redundancy index using random geometric graphs and clustered graphs in simulations. (C) 2016 Elsevier B.V. All rights reserved.
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    Input Constraints in Formation Control of Mobile Robots
    (Kırıkkale Üniversitesi, 2021) Kılıçarslan Ouach, Meral; Eren, Tolga
    The paper investigates the better possible combined initial conditions of leader-follower formations of nonholonomic mobile robots for Input/Output Linearization Technique. Initial conditions are applied to two followers and one leader robot. The first follower tries to maintain desired distance and angle towards the leader while the second follower tries to maintain desired distances to the first follower and the leader. In simulations, it is observed that, changing initial relative positions and velocities as well as angles can cause robots act differently throughout the whole leader- follower trajectory. At the end, optimum initial conditions are proposed for the best trajectory.
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    Kablosuz Sensör Ağlarında Konum Belirlemede Parçacık Sürü Optimizasyonu ve Yarasa Algoritması Yöntemlerinin Karşılaştırılması
    (Kırıkkale Üniversitesi, 2019) Doğru, Ahmet Sami; Temel, Burak; Eren, Tolga
    Kablosuz sensör ağlarında konum belirleme birçok uygulamada her geçen gün önemli bir konu haline gelmektedir. Arama kurtarma, doğal afet, coğrafi izleme ve takip gibi uygulamalarda sensörlerin konumunu doğru ve hızlı bir şekilde tespit etmek çok önemlidir. Kablosuz sensör ağlarında (KSA), konum belirleme çok boyutlu bir optimizasyon problemi olarak ifade edilmektedir. KSA’ların karmaşıklığına göre optimizasyon yöntemlerinin performansları da değişmektedir. Bu çalışmada, Parçacık Sürü Optimizasyonu (PSO) ve Yarasa Algoritması (YA) metotları KSA’larda konum belirleme probleminin çözülmesi amacı ile karşılaştırılmıştır. Önerilen yöntemler, doğada yaşayan varlıkların hareketinden esinlenerek geliştirilmiş optimizasyon yöntemleridir. Bu çalışmada sezgisel optimizasyon metotlarından olan PSO ve YA, Matlab ortamında test sistemine uygulanmış olup sonuçlar değerlendirilmiştir.
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    Kablosuz Sensör Ağlarında Konum Belirlemede Parçacık Sürü Optimizasyonu, Yarasa Algoritması, Diferansiyel Gelişim Algoritması ve Ateşböceği Algoritması Yöntemlerinin Karşılaştırılması
    (2020) Doğru, Ahmet Sami; Eren, Tolga
    Kablosuz sensör ağlarında konumlandırma birçok alanda her geçen gün önemli bir konu haline gelmektedir. Askeri uygulamalar, acil yardım, coğrafi takip gibi uygulamalarda sensörlerin yerini hata payı en düşük ve hızlı bir şekilde bulmak çok önemlidir. Kablosuz sensör ağlarında (KSA), konum tespiti çok yönlü bir optimizasyon sorunu olarak belirtilmektedir. KSA’ların kompleksliğine göre optimizasyon metotlarının verimi değişkenlik göstermektedir. Bu çalışmada, Parçacık Sürü Optimizasyonu (PSO), Yarasa Algoritması (YA), Diferansiyel Gelişim Algoritması (DGA) ve Ateşböceği Algoritması (AA) yöntemleri KSA’larda konum belirleme sorununun çözülmesi hedefi ile kıyaslanmıştır. Önerilen yöntemler, doğada bulunan canlıların karakteristiğinden ilham alınarak keşfedilmiş optimizasyon yöntemleridir. Bu çalışmada sezgisel optimizasyon yöntemlerinden olan PSO, YA, DGA ve AA Matlab ortamında bir örnek düğüm dağılımına uygulanmış olup sonuçlar gözlemlenmiştir.
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    Kablosuz Sensör Ağlarında Konum Belirlemede Sezgisel Algoritmaların Kuantum Davranışları ile Karşılaştırılması
    (2020) Kızılkaplan, Ertem; Eren, Tolga; Yalçınkaya, Fikret
    Günümüzde, kablosuz sensör ağlarında (KSA) konum belirleme giderek önemli bir hale gelmektedir. Bir çok uygulamada kullanılan KSA’larda konum belirleme optimizasyon tekniği, istenilen amaca doğru, hızlı ve de güvenilir bir şekilde ulaşmak için önemli bir adım oluşturmaktadır. Bu nedenle hedeflenen konumları bulmayı amaçlayan çalışmada, doğadan esinlenerek oluşturulmuş yeni nesil sezgisel algoritmalardan Çiçek Tozlaşma Algoritması (FPA) ve Guguk Kuşu Arama Algoritması (CSA) metotları (KSA)’larda konum belirleme probleminin çözülmesi amacı ile karşılaştırılmıştır. Ayrıca bu algoritmaların küresel arama kabiliyetini ve doğruluğunu geliştirmek ve karşılaştırmak amacıyla da Çiçek Tozlaşma Algoritması (FPA) ve Guguk Kuşu Arama Algoritması (CSA) kuantum davranışlı arama mekanizmalarıyla ayrı ayrı birleştirilmiştir. Matlab ortamında test sistemine uygulanmış kuantum davranışlı QFPA ve QCSA ile standart FPA ve CSA’nın benzer problem çözümüne olan yaklaşımları da değerlendirilmiştir.
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    Kablosuz Sensör Ağlarında Konum Belirlemede Sezgisel Algoritmaların Kuantum Davranışları ile Karşılaştırılması
    (Kırıkkale Üniversitesi, 2020) Kızılkaplan, Ertem; Eren, Tolga; Yalçınkaya, Fikret
    Günümüzde, kablosuz sensör ağlarında (KSA) konum belirleme giderek önemli bir hale gelmektedir. Bir çok uygulamada kullanılan KSA’larda konum belirleme optimizasyon tekniği, istenilen amaca doğru, hızlı ve de güvenilir bir şekilde ulaşmak için önemli bir adım oluşturmaktadır. Bu nedenle hedeflenen konumları bulmayı amaçlayan çalışmada, doğadan esinlenerek oluşturulmuş yeni nesil sezgisel algoritmalardan Çiçek Tozlaşma Algoritması (FPA) ve Guguk Kuşu Arama Algoritması (CSA) metotları (KSA)’larda konum belirleme probleminin çözülmesi amacı ile karşılaştırılmıştır. Ayrıca bu algoritmaların küresel arama kabiliyetini ve doğruluğunu geliştirmek ve karşılaştırmak amacıyla da Çiçek Tozlaşma Algoritması (FPA) ve Guguk Kuşu Arama Algoritması (CSA) kuantum davranışlı arama mekanizmalarıyla ayrı ayrı birleştirilmiştir. Matlab ortamında test sistemine uygulanmış kuantum davranışlı QFPA ve QCSA ile standart FPA ve CSA’nın benzer problem çözümüne olan yaklaşımları da değerlendirilmiştir.
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    Localization with Particle Swarm Optimization, Continuous Time Ant Colony Algorithm and Vortex Search Algorithm Methods in Wireless Sensor Networks
    (Kırıkkale Üniversitesi, 2021) Çakıcı, Feyza Nur; Eren, Tolga
    Today, with the increase in usage areas of wireless sensor networks (KSA), it is becoming an important issue. Sensor nodes are used in many applications such as monitoring the movements of living thing in natüre, smart home systems, weather forecasts, military operations, health areas. As the usage areas of KSA’ s increase, it is important to determine the location of the sensors accurately, quickly and reliably. Determining the location of KSA’ s is considered as an optimization problem and many different optimization methods have been used to determine the with the least error. The article compares the results obtainde using Particle Swarm Optimization (PSO), Ant Colony Optimization for Continuous Domains (ACOR) and Vortex Search Algorithm (GAA). It is applied to the test system in Matlab environment and the results are expressed in tables.
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    Localization with Particle Swarm Optimization, Continuous Time Ant Colony Algorithm, Vortex Search Algorithm, Invasive Weed Optimization Algorithms with Wireless Sensor Networks and K-Connectivity Analysis
    (Kırıkkale Üniversitesi, 2021) Çakıcı, Feyza Nur; Eren, Tolga
    Wireless sensor networks (WSN) are used in many different fields. It is important to determine the location of the information received so that the information becomes meaningful in the applied areas. Different methods have been used to determine the location of WSN’s. Even if any of the nodes in the WSN are disabled, communication in the network shouldn’t be disrupted. In this case, k-connectivity is an important point for the network. In the article, Particle Swarm Optimization (PSO), Ant Colony Optimization for Continuous Domains (ACOR), Vortex Search Algorithm (VSA), and Invasive Weed Optimization (IWO) the location of the sensor nodes are determined using. The k-connectivity is calculated based on the transmission distance (R). The average error in the localization is examined by applying k-connectivity to the algorithms in the Matlab environment, and the simulation results are shown in tables and figures.
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    PRM Path Smoothening by Circular Arc Fillet Method for Mobile Robot Navigation
    (Kırıkkale Üniversitesi, 2024) Kılıçarslan Ouach, Meral; Eren, Tolga; Özcan, Evrencan
    The problem of motion planning and navigation for mobile robots in complex environments has been a central issue in robotics. Navigating these environments requires sophisticated algorithms that handle obstacles and provide smooth, efficient paths. The Probabilistic Roadmap (PRM) method is a widespread technique in robotics for constructing paths for mobile robot navigation. In this study, we propose a novel path-smoothing method using arc fillets for path planning, building on PRM's foundation in the presence of obstacles. Our method operates in two primary stages to improve path efficiency and quality. The first stage generates the shortest path between the initial and goal states in an obstacle-rich environment using PRM, constructing a straight-line, collision-free route. The second stage smooths corners caused by nodes with arc fillets, ensuring smooth turns and minimizing abrupt changes in direction, resulting in more natural and efficient robot motion. We conducted simulations and tests using various PRM features to evaluate the proposed method. The results indicate that the built route offers a smooth turning motion and quicker, more compact movement while evading obstacles. This study contributes to mobile robot navigation by offering a practical approach to improving pathway quality in challenging environments.
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    Shape control of cyclic networks in multirobot formations
    (Tubitak Scientific & Technical Research Council Turkey, 2013) Eren, Tolga
    The first part of this paper examines cycles at the network level of sensing and control architectures that are needed to maintain the shape of a multiagent formation in 2-dimensional space, while the formation moves as a cohesive whole. The key tools used in the paper are rigidity theory and graph theory. The second part of the paper focuses on the planner level and controller level of the architecture by designing the fuzzy planner and fuzzy controller of individual agents. This permits the decomposition of the complex coordination problem into a series of smaller ones. The fuzzy planner and the fuzzy controller on kinematic unicycles are simulated for an exemplary cyclic formation generated by the results obtained in the first half of the paper. The validity of the proposed approach in the shape control of multiagent formations is verified through simulation experiments.