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  • Öge
    A stable, energy and time efficient biped locomotion
    (Lisansüstü Eğitim Enstitüsü, 2021) Yılmaz, Sabri ; Gökaşan, Metin ; 725780 ; Kontrol ve Otomasyon Mühendisliği
    This thesis presents two different walking strategies for biped robots while ensuring energy efficiency. The first strategy is a closed-loop walking controller based on the most used 3-Dimensional (3D) Linear Inverted Pendulum Model (LIPM) which is used to calculate the Zero Moment Point (ZMP) approximately. The closed-loop Proportional Integral (PI) controller's coefficients are searched by the Genetic Algorithm (GA), which is developed to overcome the 3D LIPM's dynamical insufficiency. Because of its ease of modeling, the key concept is to continue to use the 3D LIPM with a closed-loop controller. For this purpose, the biped is modeled using the 3D LIPM, which is one of the most well-known modeling approaches for humanoid robots due to its ease of use and quick computations during trajectory planning. Model Predictive Control (MPC) is applied to the 3D LIPM once the simple model is obtained to search the reference trajectories for the biped while meeting the ZMP criteria. The second strategy is to express the ZMP in a detailed model instead of an approximate model. For this purpose, the biped is modeled with the conventional robot modeling methods and the detailed expression of the ZMP is obtained. Then the problem is redefined as a Nonlinear MPC problem. The highly complicated biped model is implemented in Matlab with the use of CasADi Library which is a symbolic library and used on large symbolic solutions. The optimal control problem is solved with the Interior Point Optimizer (IPOPT), which is an optimization solver for large equations. With the solution of the optimal control problem, reference trajectories are found for the biped while satisfying the ZMP criteria. Both strategies suggested in this thesis are studied and implemented on a biped robot which means the robot has no upper body elements. The main idea is that if the dynamic flaws are suppressed without any upper body elements, this study will open a way to work on more modular robots. After obtaining two different walking strategies, the energy-efficient trajectory for the swing leg is searched to have longer working durations on the field. The Big Bang Big Crunch with Local Search (BBBC-LS) global optimization algorithm is used for energy efficiency. With the newly defined trajectory there became nearly 10% energy consumption reduction compared to the sinusoidal trajectory. To implement the algorithms to the real biped, a new communication library is written to meet the desired communication speed. But with the increased speed in communication, there became random packet losses on the feedback from the motors. These packet losses are examined and it is observed that these random packet losses may make the system unstable, so to suppress the effects of packet losses the problem is redefined as a time delay problem. With the redefinition of the problem, the well-known Smith Predictor method is used to overcome the packet losses and from the results, it can be seen that with this redefinition the instability risk because of the packet losses has disappeared. In a short summary, a two-legged robot has been modeled using conventional methods in the literature. First, the dynamic defects of the simple model are eliminated with a conventional controller. Secondly, a more detailed dynamic model is obtained. Walking planning is done with both methods and comparisons are made with the method commonly used in the literature. The success of the proposed methods has been demonstrated in both simulations and experimental results. With the two methods proposed in this thesis, the oscillation problem encountered by one of the most widely used walking models in the literature has been resolved. After obtaining stable walking, energy optimization is studied so that the robot could work longer in the outdoor environment and trajectory improvement is made to reduce energy consumption during the robot's movement. Finally, a faster communication library is written to apply the designed algorithms to the real system and to solve the problems caused by communication speeds, the problem is redefined with a different approach and the traditional method, Smith Predictor, is used. Packet losses that are random thanks to the communication interfaces prepared for the mechanism; become predictable and the effects of packet losses are eliminated with Smith Predictor. Finally, all these control methods are applied to the system and used in experimental studies.
  • Öge
    Discrete-time adaptive control of port controlled hamiltonian systems
    (Fen Bilimleri Enstitüsü, 2020) Alkrunz, Mohammed ; Yalçın, Yaprak ; 657354 ; Kontrol ve Otomasyon Mühendisliği Ana Bilim Dalı
    In control theory, the design of the adaptive controllers in the discrete-time setting for nonlinear systems has been an interesting area of research. The adaptive controller deals with the problem of finding an appropriate and efficient control structure with an adaptation mechanism to preserve stability and an acceptable closed-loop performance in the existence of a considerable amount of uncertainties or time-varying parameters. It is well known that nonlinear systems are sensitive to disturbances, unknown noises, and parameter perturbations. For these kinds of perturbed systems, adaptive control theory is a powerful tool to establish compensation procedures in an effective way that automatically updates the controller to improve the performance of the controlled systems. This thesis study considers adaptive control of an important class of nonlinear systems so-called Port-controlled Hamiltonian systems (PCH) with uncertainty in their energy function and proposes adaptive discrete-time controllers with novel construction of parameter estimators for the multiplicative uncertainty case, the linearly parametrized case, and the nonlinearly parameterized case. The proposed method adopts the Interconnection and Damping Assignment Passivity-based control (IDA-PBC) as the control design method and the Immersion and Invariance (I&I) for parameter(s) estimation. Therefore, the two approaches, namely, the IDA-PBC and I&I techniques, are combined in a discrete-time framework such that all the trajectories of the closed-loop system are bounded, and system states successfully converge to the stable desired equilibrium points, namely the minimum of the desired energy function. As mentioned previously, the Immersion and Invariance (I&I) approach is considered to develop an automatic tuning mechanism for the adaptive IDA-PBC controller. To comply with I&I conditions, for each case, the estimation error dynamic is defined such that it includes a free design function of the system states, and then the parameter estimator is constructed by establishing a parameter update rule and by presenting a novel function for the mentioned free design function such that Lyapunov stability of the estimator error dynamics is ensured. This novel design function includes some parameters, that can vary in a determined range, to provide the ability to assign desired dynamics to the estimator error system. By replacing the uncertain terms with the values obtained by the I&I estimator, the closed-loop system is immersed in the desired closed-loop system which would be obtained with the IDA-PBC controller with true parameters. In the multiplicative uncertainty case, and as an initial formulation of this study, the uncertainties in energy function appear as multiplicative uncertainties to the gradient of the Hamiltonian function. Unlike the other two formulation cases, no specific perturbation is considered in the system parameters and instead, a general multiplicative uncertainty is presented to the gradient of the Hamiltonian function and thus the adaptive IDA-PBC controller is constructed considering this multiplicative uncertainty formulation. The I&I based estimator is designed by selecting an update rule and presenting a general structure for the free design function such that the estimator error dynamics are Lyapunov asymptotically stable. The proposed general structure includes a free parameter that enables to assign different desired dynamics to the estimator. By including the proposed estimator in the constructed adaptive IDA-PBC controller, the local asymptotic stability of the obtained closed-loop system is shown in a sufficiently large set. One underactuated Hamiltonian system example is considered. In the linear parameterized case, the uncertainties of system parameters appear linearly in the energy function and thus the uncertain system dynamics are formulated such that these uncertainties appear in linearly parameterized form in the gradient of the Hamiltonian function. By considering this formulation of the linear parameterization of the uncertain system parameters, the adaptive IDA-PBC controller is constructed. Since PCH is linearly parameterized in the proposed formulation, the gradient of the Hamiltonian function could be factorized in two terms such as one of the terms becomes a matrix that includes all the known terms of system states and system parameters while the other term is a vector of unknown parameters. The mentioned matrix can be a full column rank or not. In the case where this matrix is full rank, the Lyapunov asymptotic stability of the estimator is proved while the Lyapunov stability of the estimator is shown for the case when it is not full rank. It is also shown that, for the case of having not full rank matrix, the term representing the effect of uncertainties in the closed-loop system dynamics obtained with the IDA-PBC controller that uses the estimated parameters approaches to zero. Furthermore, the Lyapunov asymptotic stability of the obtained closed-loop system is shown in a sufficiently large local set either the matrix is full rank or not. For the I&I based estimator design, a general structure for the free design function that includes some free parameters is presented that makes the estimator error dynamics Lyapunov stable where these free parameters are in a determined specific range. So that, by selecting different values for these free parameters in the determined range, different desired dynamics can be assigned to the estimation of each unknown parameter. Three linearly parameterized examples are considered; two fully actuated systems (One has a formulation with a full rank matrix while the other has a formulation with a not full rank matrix), and one underactuated system. In the nonlinear parametrized case, the parameter uncertainties that appear nonlinearly in the energy function are considered. A proper formulation for uncertain system dynamics is presented such that the uncertainties appear in non-linearly parameterized form in the gradient of the Hamiltonian function and the adaptive IDA-PBC controller is constructed considering this formulation. The conditions on the Lyapunov asymptotic stability of the estimator dynamics are derived. Namely, it is proved that if these conditions are satisfied, the estimator error dynamics become asymptotically stable. Assuming these conditions are satisfied, local asymptotic stability of the closed-loop system, which is obtained when the proposed estimator is used with the adaptive IDA-PBC controller, in a sufficiently large set is proved. For the I&I based estimator design, a structure for the free design function of the estimator is proposed including some other free design functions to satisfy these conditions however it is seen that it is not easy to give general suggestions for these last free functions. It is concluded that for each example, a special selection of these functions is needed. Two nonlinearly parameterized examples are considered and proper selections of the free design functions in the proposed structure is performed. One of the example is a fully actuated mechanical system while the other one is under-actuated. The simulation results for each of the previously mentioned systems illustrated the effectiveness of the proposed adaptive controller in comparison to the non-adaptive controller for the same test conditions. The estimator successfully estimates the uncertain parameters and the adaptive IDA-PBC controller that utilizing these parameters stabilizes the closed-loop system and preserves the performance of the stable desired Hamiltonian systems.
  • Öge
    Analysis and design of general type-2 fuzzy logic controllers
    (Fen Bilimleri Enstitüsü, 2020) Sakallı, Ahmet ; Kumbasar, Tufan ; 656903 ; Kontrol ve Otomasyon Mühendisliği Bilim Dalı
    This thesis presents new interpretations on the design parameters of the general type-2 fuzzy logic controllers by investigating their internal structures, proposes novel systematic design approaches for the general type-2 fuzzy logic controllers based on comprehensive and comparative analyses, and validates theoretical findings as well as proposed tuning methods via simulation and real-time experiments. The fuzzy systems have been successfully realized in a wide variety of engineering areas such as controls, image processing, data processing, decision making, estimation, modeling, and robotics. The fuzzy logic systems provide complex mappings from inputs to outputs, and this benefit usually results in better performances in comparison to non-fuzzy counterparts. Due to this, the fuzzy logic controllers have been applied to numerous challenging control problems for decades. Nowadays, more attention has been given to a new research direction of the fuzzy sets and systems, the general type-2 fuzzy logic controllers, which is the main motivation of this thesis. The internal structures of a class of Takagi-Sugeno-Kang type fuzzy logic controllers are first examined in detail. In this context, three fuzzy logic controller types (type-1, interval type-2, and general type 2) and two kinds of controller configurations (single-input and double-input) are considered. The baseline controllers, i.e. type-1 and interval type-2 fuzzy logic controllers, are presented in the preliminaries section. The fuzzy sets, fuzzy relations, fuzzy rules, fuzzy operators, and PID forms of these fuzzy logic controllers are explained in detail. The design assumptions and design parameters are given, also the most common design approaches are listed. Afterward, the general type-2 fuzzy sets and the general type-2 fuzzy logic controllers are presented. The general type-2 fuzzy logic controllers are described with α-plane associated horizontal slices because the α-plane representation provides useful advantages on the handling of the secondary membership function of the general type-2 fuzzy sets and the calculation of the general type-2 fuzzy logic controller output. It is shown that the α-plane based general type-2 fuzzy logic controller output calculation is accomplished through the well-known interval type-2 fuzzy logic computations. The secondary membership functions are further detailed in terms of their mathematical definitions and design options. The structure analysis on the general type-2 fuzzy sets shows the interactions between non-fuzzy, type-1 fuzzy, interval type-2 fuzzy, and general type-2 fuzzy sets happen in the secondary membership function. It is shown that the general type-2 fuzzy logic controller can easily transform into interval type-2 fuzzy, or type-1 fuzzy counterparts based on the secondary membership function definitions. As an outcome of this structural analysis, a new representation of the trapezoid secondary membership function is proposed based on a novel parameterization of the parameters that form the trapezoid shape. It is shown that the parameterized trapezoid secondary membership function is capable to construct trapezoid, triangle, interval, and singleton shapes so that the general type-2 fuzzy logic controllers are further capable to transform into interval type-2 fuzzy, or type-1 fuzzy counterparts. It is also shown that the proposed parameterization of the trapezoid secondary membership functions allows designing the control curves/surfaces of the general type-2 fuzzy logic controllers with a single tuning parameter. Moreover, the structural design suggestions are presented not only to construct fuzzy controllers in a straightforward manner but also to ease the design of the controllers with few design parameters. The design parameters of the general type-2 fuzzy logic controllers are grouped as the shape and the sensitivity design parameters with respect to their effects on the accuracy and the shape of the resulting fuzzy mapping. Accordingly, the tuning parameter of the secondary membership functions and the total number of α-planes are interpreted and as the sensitivity and shape design parameters, respectively. The shape analyses of the general type-2 fuzzy logic controllers show the effects of the proposed shape design parameter on the control curves/surfaces. In this context, the resulting fuzzy mappings of single input and double input general type-2 fuzzy logic controller structures are compared for various design settings of the shape design parameter. The comparative analyses provide interpretable and practical explanations on the potential advances of the shape design parameter. Based on the shape analyses, novel design approaches are proposed to tune the shape design parameter in a systematic way. In this context, it is suggested constructing the general type-2 fuzzy logic controllers over their type-1 and interval type-2 baselines and tuning them via the shape design parameter by providing a tunable tradeoff between robustness and performance. Therefore, it is aimed to combine benefits of baseline type-1 (relatively more aggressive control curves/surfaces better performance measures) and interval type 2 (relatively smoother control curves/surfaces, better robustness measures) fuzzy logic controllers. To enhance the control performance, two scheduling mechanisms are also proposed for online-tuning of the shape design parameter with respect to the steady-state operating points as well as transient-state dynamics. The sensitivity analyses of the general type-2 fuzzy logic controllers show the effects of the proposed sensitivity design parameter on the accuracy of the control curves/ surfaces. In this context, the resulting fuzzy mappings of single input and double input general type-2 fuzzy logic controller structures are also compared for various design settings of the sensitivity design parameter. The comparative sensitivity analyses show interpretable and practical explanations of the sensitivity design parameter in terms of calculation accuracy and computation burden. Therefore, it is suggested tuning the sensitivity design parameter by considering the limitations of hardware components such as resolution and processing speed. To accomplish the design in accordance with a tradeoff between sensitivity and computational time, a novel iterative algorithm is proposed to tune the sensitivity design parameter. The simulation and real-time experimental control studies validate the proposed design recommendations, systematic design approaches, and tuning methods for the general type-2 fuzzy logic controllers on benchmark control systems. In these control studies, the general type-2 fuzzy logic controllers are designed based on the proposed design methods. In order to show the performance improvements on the control systems, the general type-2 fuzzy logic controllers (tuned either online or offline) are compared with type-1 fuzzy and interval type-2 fuzzy counterparts. The performance measures clearly show that the online-tuned general type-2 fuzzy logic controllers outperform all general type-2, interval type-2, and type-1 counterparts on account of the proposed scheduling mechanisms over the proposed systematic design rules. The results also show that the systematic design of the general type-2 fuzzy logic controllers is simply accomplished by following the proposed tuning steps of the shape and sensitivity design parameters.
  • Öge
    Active slam with informative path planning for heterogeneous robot teams
    (Fen Bilimleri Enstitüsü, 2020) Akay, Mehmet Caner ; Temeltaş, Hakan ; İnsansız Hava Aracı'nı (İHA'yı) ve İnsansız Kara Aracı'nı (İKA'yı) bünyesinde bulunduran heterojen yapılı robot takımları, günümüzde gözetleme, takip, keşif, vb. farklı görevlerde kullanılmaktadır. Çevrenin haritalanmasını gerektiren keşif görevlerinde, heterojen robot takımlarının ortamı daha iyi anlayabilmesi adına, ortak bir haritaya ihtiyaç duyulmaktadır. Bu doğrultuda özel yaklaşımlarla, Lidar Odometre ve Haritalama (LOH) ile zorlayıcı yapıların bulunduğu ortamda, araçların kooperatif bir şekilde benzerlik metriklerini kullanarak ortak harita çıkarması sağlanmaktadır. Bunun yanı sıra, sınırları belirli bir alanın, heterojen robot takımları ile keşfini sağlamak adına sürekli olarak toplanan bilgiyi arttırıcı kontrolcü tasarımı kullanılmaktadır. Farklı tipte hareket denklemlerine ya da dinamik modellere ve/veya farklı sensör yapılarına sahip robotlardan oluşan robot takımlara heterojen yapılı robot takımları denmektedir. Diğer taraftan robot takımlarının eş zamanlı konumlama ve haritalama problemi ile bu takımdaki robotların yol planlamalarının eş zamanlı gerçeklemesi ise Aktif eş zamanlı konumlama ve haritalama (EZKH) problemi olarak adlandırılmaktadır. Buradaki eş zamanlı gerçeklemedeki amaç otonom robot araçları için planlanan yolların aynı zamanda EZKH'deki belirsizliği de minimize edecek şekilde gerçekleştirilmesidir. Diğer bir deyişle otonom robot araçları için bilgilendirici yol planlarının oluşturulmasıdır. Bu çalışmanın temel amacı heterojen yapılı robot grupları için bilgilendirici yol planlamaya dayalı bir Aktif-EZKH sistemi tasarlamaktır. Robot takımlarının farklı dinamik ve sensörlere sahip olması diğer bir deyişle heterojen yapıda olmaları, bu robot takımlarına avantajlar getirmektedir. Örneğin; hava robotları hızlı hareket edebilir, kara robotları daha ağır faydalı yükler taşıyabilir ve hedef nokta ile doğrudan etkileşime girebilirler. Karma bir araçlı bir yapı içerisinde yer alan İHA ile İKA oluşan bir robot grubu keşif, arama veya güvenlik amaçlı sınırları belirlene bir bölge içinde iş birliği yaparak ortam içindeki görevlerini insandan bağımsız bir şekilde otonom olarak gerçekleyebilir. Burada İHA ve İKA'ların birbirleri ile yer istasyonu aracılığı ile veri paylaşımında olduğu varsayılmaktadır. Komşuluk alanları içerisinde haberleşme ile harita paylaşımı ya da araç durum vektörü paylaşımı yapabilen robot birimleri kooperatif robotlar olarak gösterilmektedir. Bu çalışmada dış ortam sensörü olarak 360° ortam taraması yapabilen ve saniyede 300.000 adet noktanın mesafesini ölçebilen 3B LIDAR sistemi kullanılmıştır. Yüksek çözünürlüklü ölçüm avantajının yanı sıra bu kadar büyük miktardaki veriden optimum miktarda ve hızlı bir şekilde anlamlı veri üretip bunları robot konumlama, planlama ve koordinasyonunda kullanım da ayrı bir zorluk ortaya koymaktadır. Temel olarak, hareketli olan bir araçtan elde edilen nokta bulutunun coğrafik olarak yerleştirilmesi gerekmektedir. Bu işlem sadece Lidar sensörü kullanılarak da; farklı sensörlerin verilerinin ortak bir şekilde kullanılması aracılığıyla da yapılabilir. SadeceLidar ile toplanmış verilerin işlenerek nokta bulutunun coğrafik olarak yerleştirilmesi ve gözlem sırasında sensörün hareketinin elde edilmesi, bu çalışmada LOH ile sağlanmaktadır. Bu sayede; GPS ve IMU olmaksızın EZKH yapılabilmektedir. Buna ek olarak, sensörlere binen gürültülerden dolayı oluşabilecek kaymalar ve yanlış veri elde edilmesi engellenebilmektedir. Buna karşılık, GPS, enkoder ve IMU verileri ile Lidar verileri birleştirilerek Genişletilmiş Kalman Filtresi (GKF) konumlaması da sağlanabilmektedir. Burda sensör verilerinin olasılıksal yaklaşımlarla işlenmesi ile robotun konumu elde edilmektedir ve bu konum ile Lidar verilerinin coğrafik yerleştirme yapılması sonucunda da belirli bir orijine sabitlenmiş nokta bulutu çıktısı alınmaktadır. Sonrasında da bu nokta bulutu ile istenilen yöntem ile elde edilen odometre ve nokta bulutu verisi farklı haritalama yöntemleri kullanılarak ayarlanabilir özel görsel çıktılar sağlanabilmektedir. Bunlardan biri, sekizli ağaç yapıları kullanılarak elde edilen OctoMap olmaktadır. OctoMap yöntemi, tez çalışmasında kullanılmasının temel sebepleri olan, çözünürlük ayarlaması, doluluk olasılığı üst ve alt sınırları belirlenmesi ve 3B olarak sağlanabilmesi açısından faydalı bir araç olmaktadır. Bu yöntem ile, ortamın uyarlanabilir şekilde, ortamın 3B haritasının çıkarılması sağlanmaktadır. Lidar sensörlerinin havadan alınan nokta bulutları ile karadan alınan nokta bulutları farklı geometrik özellikler taşımaktadır. Ancak, hava ve kara Lidar görüntülemesinin birbirlerini tamamlaması bakımından oldukça büyük avantajları da mevcuttur. Hava aracı ve kara aracı tarafından yapılan ve birilerinin göremedikleri bölgelerin görüntülenebilmesi sağlanılmaktadır. Bu avantajı kullanabilmek adına farklı açılardan lokal olarak görüntülenen ortamın ortak bir haritada birleştirilmesi gerekmektedir. Harita birleştirme adımını gerçekleştirmek adına her iki robotun elde ettiği verilerden ortak olanını belirlemek gerekmektedir. Kuş bakışı veya yatay olması fark etmeksizin bir nesnenin yere göre yüksekliği; hem havadan hem karadan yapılan gözlemlerde sensörlerin görüş açısı sınırları içerisinde aynı olacaktır. Bu doğrultuda, yükseklik verileri üzerinden benzerlik metrikleri kullanılarak haritaların birleştirilmesi sağlanabilmektedir. Bu tez çalışmasında, İHA ve İKA tarafından elde edilen nokta bulutu ızgara haritasına benzer bir yapıda olan yükselti haritaları kullanılmıştır. Izgaralar ile bölünmüş hücrelerdeki en yüksek noktanın verisinin kullanılması ile 2.5D harita elde edilmesi sayesinde yükselti haritaları oluşturulmaktadır. Benzerlik metrikleri aracılığıyla ise bu haritadaki yükseklik bilgilerinin birbirine oturmasını sağlayacak konum ve yönelim farkı belirlenmektedir. Çalışmanın sonraki aşamalarında entropi teorisi kullanılması sebebiyle entropi temelli benzerlik metrikleri ile harita birleştirme yapılmıştır. Yedi farklı tipteki entropi metriği ile yapılan benzerlik karşılaştırması sonucunda "Jensen Divergence" entropi tanımının en az hata ile haritalar arasında dönme ve öteleme farkının belirlenmesini sağladığı, deneyler ile doğrulanmıştır. Ayrıca; haritanın dikey eksende katmanlara ayrılması ve bu katmanlar üzerinden yapılan yükseklik benzerlikleri hesaplaması ile optimum konum ve yönelim ( veya dönme ve öteleme) farklarının belirlenmesinin; katmanlara ayırma metodunun kullanılmasına göre daha avantajlı olduğu da gösterilmiştir. Her bir otonom araç "Harita Birleştirme" süreci sonrasında bu harita Aktif-EZKH süreci için kullanılarak hem harita bilgileri daha hassas hale getirilir hem de robotun gitmesi gereken yeni konumu tespit edilmiş olur. Yol planlaması, görevin etkin bir şekilde icrası için gerekli olan kritik adımlardan biridir. Enerji tüketim, elde edilen sonucun gerçekleşme süresi ve kalitesi uygulamanın ana kriterleridir. Bu nedenle, yol planlama algoritmaları etkin sistemler oluşturmak üzere kullanılmaktadır. Yol planlama algoritmaları farklı türde olabilir ama özelliklehedef işaretleme ve bilgi maksimizasyonuna dayalı yöntemler diğer yol planlama yöntemlerine göre belirgin üstün özelliklere sahip olanlarıdır. Hedef odaklı yol planlama algoritmalarında, birimlerin belirli bir hedefe ulaşabilmesi adına oluşturduğu kontrol eylemleri bulunmaktadır. Bilgi maksimizasyonu yaklaşımı; ortam, nesnenin diğer nesneler veya bir hedef hakkında daha fazla bilgi almak için bir doğrultu boyunca hareket etmesi olarak tarif edilebilir. Burada bağıl entropi teorisi, bilgi maksimizasyonu yaklaşımı olarak sunulmuştur. İlaveten, bağıl entropi, karşılıklı bilgi ile çevresel durum entropisiyle arasındaki farktır. Bağıl entropi kullanılarak, bilgi metrik olarak ifade edilebilmektedir. Çevresel durumlar ile gözlemler ile elde edilen durumlar arasındaki bağıl entropi üzerinden yaratılan amaç fonksiyonunun optimal çözümü sonucunda elde edilen hedef nokta, o bölgedeki bilginin belirlenen kriterlere göre istenilen seviyeye çekilmesini sağlamaktadır. Bu, EZKH ile etkileşimli çalışan yol planlaması temelli bir optimal kontrol yöntemidir. Bu yöntem çerçevesinde Bilgi Teorisinden faydalanılarak belirsizlik terimleri ile entropi terimleri arasında ilişki kuran bir Karşılıklı Bilgi terimi tanımlanır. Kulback-Liebler Mesafesi olarak da tanımlanan bu Karşılık Bilgi terimi maksimum değerine ulaştığında belirsizleri temsil eden entropi terimleri de minimize olurlar. Bu sebeple Karşılık Bilgi terimine dayalı bir amaç fonksiyonu oluşturularak bu fonksiyonu maksimize yapacak robot konum ve hareket vektörleri optimal kontrol yaklaşımı ile elde edilir. Bu elde edilen terimler heterojen robot takımında yer alan otonom robotlara uygulanarak onların hareketleri planlanmış olur. Amaç fonksiyonunu Lyapunov kararlı yapan bu noktalar ise bir hacimsel bölgenin merkezidir ve bu hacimsel bölgedeki bilgiyi maksimize etmek üzere belirlenmiştir. Bu noktaya ulaşmak için, robotlar belirlenen kurallar çerçevesinde hareket etmektedir. Bu kurallar ise İHA veya İKA'nın hedef noktaya hareketinin seçimi ve hedef noktaya ulaşım için engellerden kaçınmayı içermektedir. Bu yöntemin; özellikle farklı boyutlarda nokta bulutu ölçümü yapabilen hava be kara araçlı robot takımındaki uygulamaları literatürde mevcut değildir. Bu teorik çalışmaları ön plana alan çalışmaların çıktılarının özellikle arama-kurtarma, keşif ve güvenlik gibi robot takımı uygulamaları için büyük önem taşıyacağı değerlendirilmektedir. Önerilen yöntemde, ortamdan yapılan ölçümler ile araç hareketlerinde oluşabilecek belirsizliklerini etkilerini en aza indiren kara ve hava robotlarından oluşan heterojen yapılı robot takımlarının keşif amaçlı yol planlama algoritmalarının geliştirilmesi ve performanslarının test edilmesi hedeflenmiştir. Aynı zamanda, bu görevleri icra edebilmek adına belirli harita birleştirmenin de gerçekleştirilmesi gerekmektedir. Öncelikle; harita birleştirilmesi yönteminin doğrulanması adına üniversite kampüsünde belirli bir bölgede kara aracı olarak Clearpath Husky A200, hava aracı olarak ise DJI Matrice 600Pro ve bu araçlar üzerinde bulunan Lidar sensörü kullanılmıştır. Sonuç olarak; teorik çalışmalarda verilen benzerlik metriklerinden en optimum olanı deneyler aracılığıyla belirlenmiştir. Sonrasında; bilgilendirici yol planlama yönteminin doğrulanması amacıyla Robot İşletim Sistemi ("ROS") ve Gazebo temelli, karmaşık ancak günlük yaşantıda karşılaşılabilinen bir simülasyon ortamı kurulmuştur. Bu simülasyon ortamında altı farklı durum yaratılarak heterojen robot takımları için bilgilendirici yol planlamalı Aktif EZKH gösterilmiş ve parametre ayarlamaları ile uygulamaya göre değiştirilebilir bir yapı sağlanmıştır. ; 650277 ; Kontrol ve Otomasyon Mühendisliği Ana Bilim Dalı
    Recently, heterogeneous teams consisting of unmanned ground vehicles and unmanned aerial vehicles are being used for different types of missions such as surveillance, tracking, and exploration, etc. Exploration missions with heterogeneous robot teams should acquire a common map for understanding the surroundings better. The unique approach presented in this dissertation with cooperative use of agents provides a well-detailed observation over the environment where challenging details and complex structures are involved. Also, the presented method is suitable for real-time applications and autonomous path planning for exploration. Lidar Odometry and Mapping with various similarity metrics such as Shannon Entropy, Kullback-Liebler Divergence, Jeffrey Divergence, K Divergence, Topsoe Divergence, Jensen-Shannon Divergence and Jensen Divergence are used to construct a common height map of the environment. Furthermore, the given layering method that provides more accuracy and a better understanding of the common map. All of the given similarity metrics are compared, and the advantage of utilizing the layering method is shown. The best similarity metric for constructing a heterogeneous robot team common map of the experimental area was obtained by using the Jensen Divergence similarity metric and layering method. Moreover, Extended Kalman Filter localization and OctoMap techniques are utilized to create an adaptive simultaneous localization and mapping infrastructure for informative path planning. Optimal parameter tuning for the specified simulation environment provides adjustable memory allocation and exploration performance, such as; duration, collected information and effort. The information seeking controller obtained with the use of relative entropy ensures exploration of the given area to minimize the uncertainty between observed states and environmental states. Robots move to the volumetric spaces' center under given rules and collect measurements by proprioceptive and exteroceptive sensors. With the use of heterogeneous robot teams, the measurements collected by the Lidar provide an advantage in perceiving complex details that can not be done by homogeneous robot teams. Constructing common map part of the theoretical approaches in this thesis are experimentally validated. In addition, the complete demonstration of this dissertation is done with six different cases by simulation studies. The theoretical background of active simultaneous localization and mapping with informative path planning for heterogeneous robot teams are validated, and the advantages of this study are remarked.
  • Öge
    Multi-agent coverage control with adaptation to performance variations and imprecise localization
    ( 2020) Turanlı, Mert ; Temeltaş, Hakan ; 637482 ; Kontrol ve Otomasyon Mühendisliği Ana Bilim Dalı
    In this thesis, an adaptive collaboration approach for a multi-agent system consisting of nonholonomic wheeled mobile robots is proposed. The positions of the agents are not known precisely but their locations are known to be within uncertainty circles. For the collaboration among the robots, the workspace partitioning algorithm is chosen as Guaranteed Power Voronoi Diagram (GPVD or GPD) which not only takes the localization uncertainty into account but also is capable of changing the regions of the generator points with respect to corresponding weight parameters. Also, the assumption is that the actuation capabilities of the robots are different from each other. The agents do not know those parameters related to their actuation performances beforehand. The contribution of the thesis is that the performance parameters of the agents are learned online by the proposed adaptive estimator algorithm and Hopfield Neural Network (HNN) estimator under localization uncertainty. The proposed algorithm is based on the coverage control which performs collaboration among the robots by assigning the regions from the workspace according to their actuation performances automatically. The definition of the actuation performances is different capabilities of the agents. The examples of strong actuation performances may include powerful motors and favorable terrain while wheel slip and weak motors can be counted as examples for the weak actuator performances. The proposed multi-agent collaborative coverage algorithm learns the performance parameters of the robots by using two approaches proposed in the thesis. The first approach is based on an adaptive estimator with a non-holonomic estimation model. The second method uses an HNN estimator. The theoretical proof, analysis and verification of the aforementioned methods are given in the related sections. After estimating the performance parameters, the weights are calculated using a neighbor based weight estimation algorithm. The weight variables are utilized in the GPD algorithm so that the workspace is partitioned according to the performance parameters of the agents in a guaranteed sense. At the end, the agents take regions from the workspace according to their actuation performances and achieve the optimal collaborative coverage so that the agents with strong actuators take larger regions from the environment than the agents with poor actuators. Thus, the collaborative coverage algorithm enables the robots to deploy themselves to an optimal configuration which minimizes the total coverage cost by taking imprecise localization into account. Moreover, a multi-agent coverage collaboration method with an energy-efficient optimal coverage control law and Hopfield networks is proposed in the related section. By using the algorithm a trade-off between coverage time and energy consumption among agents can be done. Meanwhile, the collaboration is achieved according to the actuation performances of the agents. The theoretical results are verified with MATLAB and ROS/Gazebo simulations and experiments that show the efficiency of the algorithm. The ROS implementation of the algorithm is explained. The experimental results are given in the related section.