Department of Mechatronics Engineering

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http://hdl.handle.net/20.500.11905/1218

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AUTOMATED CLUSTERING OF BEHAVIOUR MODULES FOR SOCIAL ROBOTS
(2023-01-27) AL-ZUABIDI, Muneer Mohammed Adnan; ERDEN, Zühal
This thesis presents a method for automatically generating behaviour modules for social robots using clustering algorithms. Behavioural modules are considered a vital element of social robot family design which falls in the benefit of individual’s needs. The work includes the implementation of different clustering techniques such as K means, Agglomerative Clustering, and BRICH to cluster behavioural elements of social robot which are categorized as "perception", "cognition" and "motoric action". In this thesis, a previously generated data list consisting of linguistic values from these elements in size of 28 by 3 is used. A mapping method is developed to represent the data in numeric form. Also, a 3D graphical representation of the data is obtained. In addition, a variety of behavioural modules are generated and evaluated using right clustering algorithms, three algorithms of which are decided as successful. The generated modules are evaluated based on four criteria as, cost, mobility, complexity, and power consumption. The results of this work can be used by researchers and engineers in the field of social robotics particularly during the conceptual design of personalized social robots. Additionally, the proposed criteria and visualization techniques can be used as a starting point for future research in this area.
A MULTI-CRITERIA DECISION MAKING APPROACH FOR ROBOT SELECTION IN A MANUFACTURING ENVIRONMENT
(2022-06-10) ARSLAN, Rasim Atakan; ERDEN, Zuhal; BAÇ, Uğur
In this thesis, we apply SWARA-WASPAS method as a multi-criteria decision making (MCDM) method for selecting the most suitable mechatronic systems to be used for the conversion of human-based production lines to production lines with robot-based automation systems. Robots are becoming not only quicker and more precise than people, but they are also frequently more cost-effective in the long term. Getting high efficiency from the robots used for different missions and choosing the most suitable robot are among the most difficult problems. To select the most suitable systems among different alternatives, SWARA-WASPAS hybrid decision making method, which suggest making the most appropriate choice among different alternatives by considering different criteria and the opinions of different experts, is applied according to the characteristic criteria of these systems, and a sensitivity analysis was carried out. As a result of the thesis, the most suitable robots from each robot selection problem are determined and it is seen that the most suitable robot is not change with the sensitivity analysis made for each robot class, but the other alternatives could change depending on the combined optimality coefficient value used.
DESIGN OF TWO WHEELED TWIN ROTORED HYBRID ROBOTIC PLATFORM
(2010-07-27) KÜÇÜK, Doğanç; ARIKAN, Kutluk Bilge; İRFANOĞLU, Bülent
The design of the two wheeled twin rotored hybrid robot (TWTR) structure is explained in the thesis. This study is the initial phase of the project to reach a hybrid platform that can navigate on ground and hover and navigate in air whenever necessary. This initial phase includes the design of the initial version of the physical system and design of basic controllers depending on the mathematical models and simulations. The system is designed and physically constructed based on the mechatronics design principles. Selection of actuators, sensor set, and the control hardware and the physical structure design are all considered simultaneously with the mathematical model and controller design phases. Nonlinear equations of motion of the physical system are derived and linearized in state space form for both ground and flying modes of motion. Linear Quadratic Regulator (LQR) and Error Space Approach type of controllers are designed employing the mathematical model and simulations. For ground motion, LQR and Error Space Approach controllers are designed and implemented on the real system; whereas PID and LQR type control systems are designed and implemented for the flying motion of the real robotic platform. Stabilization of the attitude dynamics is considered for the flying motion in this study. Designed control systems are implemented on the physical system and the control parameters are tuned experimentally. The control system is developed in Matlab/Simulink and real time implementation is achieved by using Simulink Real Time Windows Target utility. Embedded controllers are not utilized in this first stage. Control systems are designed for the stabilization of the system and error space approach is applied for tracking a reference for the motion of the robot on ground. LQR’s are designed to stabilize the attitude dynamics of the robot for flying motion. Switching between the control systems on ground and in air modes are achieved using a proximity sensor that can sense the distance of the platform body to the ground. Experiments show that system can be stabilized on ground and the attitude dynamics can be stabilized in air. The system will be developed to fully guide on ground and in air.
DESIGN OF A MODULAR EDUCATIONAL SET-UP FOR MECHATRONICS ENGINEERING
(2013-03-22) AYHAN, Emre; ERDEN, Zühal
This thesis is a study on modular mechatronic product design. The main purpose of this study is to implement heuristic approach to the modular design of a mechatronic product family. The heuristic method has been developed and applied for the design of mechanical product families. Thus, main contribution of this thesis is the application of the method in the mechatronic design field. In this study, the selected product family is an educational mechatronic set-up which will be used for the sophomore mechatronics design course in the Mechatronics Engineering Department of Atılım University. This research includes implementation of the heuristic design methodology and conceptual design for the mechatronics educational set-up, as well as its physical design and manufacturing.
ATTITUDE AND ALTITUDE CONTROL OF TWO WHEEL TRIROTOR HYBRID ROBOT
(2013-05-21) ALWAFI, Husein; İRFANOĞLU, Bülent; ARIKAN, Kutluk Bilge
Two Wheel Tri-Rotor (2W3R) hybrid robot that can move on ground, hover and navigate in air, is a novel system studied in this thesis. Physical structure of the system had been built in Flying Robotics Laboratory by undergraduate students as a course project in Mechatronics Department at Atılım University. Core of this thesis is to design controllers to stabilize and control the system on its hovering conditions. Stabilization and control of roll, yaw, pitch, and the altitude dynamics using the propulsion units are studied. Nonlinear equations of motion of the physical system are first derived, and then state feedback linearization technique and Linear Quadratic Regulator (LQR) are used, and control systems are developed in Matlab Simulink.
DEVELOPMENT OF A WALKING MACHINE WITH TWO LEGS
(2013-08-14) GOL MOHAMMAD ZADEH, Mohammad Hassan; ARIKAN, Kutluk Bilge; İRFANOĞLU, Bülent
This dissertation reports on the developments of the bipedal walking robot BIROL. Special about it is that BIROL has 12 degrees of freedom and is actuated with the servomotors which are controlled in real time mode by RTWT through Matlab/Simulink. Before designing the controller, mathematical model has been obtained using Denavit-Hartenberg convention and Newton-Euler method. We generated a dynamically consistent motion pattern off-line by using central pattern generators (CPG) first for a Test Bench Walking Robot then for BIROL Robot. In order to keep the balance of robot the motion pattern consists the desired trajectories of all joints and the desired zero moment point (ZMP) trajectory. Force sensory feedbacks give the ground contact forces to compare real system with simulation.
IMPROVEMENT OF A RC QUADROTOR PLATFORM TO A FLYING ROBOT FOR TARGET TRACKING
(2013-07-19) TANSU, Fırat; ARIKAN, Kutluk Bilge; İRFANOĞLU, Bülent
In this study, transformation of Draganfly Vi Ti Pro, a remote controlled (RC) Quadrotor platform, into a target tracking flying robot is aimed. This thesis examines controller design for the attitude and altitude dynamics and target tracking. The major aim of this work is to design a normalized linear quadratic regulator (LQR) for attitude and altitude dynamics and achieve target tracking by PID controllers on a moving object. Before designing the controller, a mathematical model has been developed using the Euler-Lagrange method. Simulations and real-time applications have been performed on MATLAB/Simulink environment. For target detection algorithm, ArUco, which is a C++ code for basic augmented reality applications, has been used. Designed controllers are implemented on the physical system and satisfactory results are achieved. Comparison of simulation with the real system has been done and discussed.
ATTITUDE AND ALTITUDE CONTROL OF A TRIPLE TILT-ROTOR UNMANNED AERIAL VEHICLE
(2013-08-13) KAÇAR, Alp; ARIKAN, Kutluk Bilge; İRFANOĞLU, Bülent
In this thesis, design of triple tilt-rotor unmanned aerial vehicle (UAV) and controller design for attitude and altitude dynamics has been studied. After UAV designed, carbon-fiber bars, plastic parts, tilt mechanisms and landing gears are manufactured. During the manufacturing process; mathematical model is obtained. The model has been linearized to design linear quadratic regulator (LQR) based controllers to stabilize the system and track reference inputs. In physical system, inertial measurement unit, ultrasonic proximity sensor, and optical flow sensor have been used to measure state variables, Brushless DC motors and high-speed servo motors are used as actuators. After completion of the simulations, real-time system tests have been started. The control algorithm designed in MATLAB, Simulink. Real Time Windows Target has been used to implement real-time control via data acquisition board. In both simulations and real-time tests attitude and altitude have been successfully controlled.
A COMPARISON BETWEEN SOFT COMPUTING METHODS AND CONVENTIONAL (PID) CONTROLLER APPLIED TO A DC MOTOR SYSTEM
(2014-06-09) DARBI, Fathi Mohamed A.; ALIEW, Fuad
This research will compare the Soft computing techniques its advantages with the optimal proportional-integral derivative (PID) controller parameters, for control of a different parameters of a DC motor. The research approach is to establish superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The methods for designing of PID Controllers will been compared and analyzed with the intelligent tuning techniques like Fuzzy Sets, Neural Networks and Genetic algorithms, Soft computing method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in position control of a DC motor.
DESIGN AND MANUFACTURING OF A DOG-LOBSTER HYBRID ROBOT AS IMPLEMENTATION OF THE “BIO- INSPIRED DESIGN METHODOLOGY” FOR INSECT / ANIMAL LOCOMOTION
(2015-01-31) GÜNER, Emre; ERDEN, Abdulkadir
This thesis includes the design and manufacturing of the hybrid robot via bio – inspired design methodology. In this thesis all the design steps of the hybrid robot are discussed. Design process of the hybrid robot separated into three parts; conceptual design, preliminary design, and detailed design. In these parts all details of the design and manufacturing phases will be discussed. In this thesis also locomotion of the dog and lobster are performed in hybrid robot. At last test procedures and test results of the hybrid robot are discussed. During this thesis study, test of the hybrid robot is performed on carrier platform, dynamic forces and other disturbances effects are ignored. As a conclusion comparison of hybrid robot with other robot and performance of the hybrid robot are discussed.
SYSTEM DESIGN AND PROTOTYPE DEVELOPMENT OF A GUIDE – GUARD ROBOT FOR THE DEPARTMENT OF MECHATRONICS ENGINEERING LABORATORIES
(2015-10-25) SADEGHİ, Amir Nobahar; ERDEN, Abdülkadir; ERDEN, Zuhal
The goal of this thesis is designing, constructing and manufacturing an autonomous, intelligent, mobile guide - guard robot and enable it to safe navigate through the indoor environments such as the laboratories of the department of Mechatronics Engineering in Atilim University. Based on the main concern of the thesis, an integrated system was designed and implemented. To accomplish the navigation task, our presented control architecture composes of localization, obstacle avoidance, path planning and robot control for steering the robot from any initial pose to arbitrary asigned pose. Our navigation architecture is a behavior-based and a mapless navigation, which the robot‟s locations are determined by observing and extracting useful features in the environment based on the onboard sensors.
TWO DEGREES OF FREEDOM FORK MOUNT ACTUATING MECHANISM DESIGN FOR OPTICAL TELESCOPE
(2015-10-23) YILDIRAN, Yaşar; NAZLIBİLEK, Sedat
The aim of this thesis is to design two degrees of freedom fork mount mechanism for optical telescopes develop the electronics, mechanics and software and to build a prototype. Telescope mount design and prototype have been done for small class optical telescopes. The mount has been able to steer optical telescopes that weigh up to 35 kilograms. Fork arms distance of the mount permits 20 to 40 cm diameter sized primary mirrors to be used. The system mechanic requirements were determined and proper design has been done. Actuators for motion and electronic hardware necessary to control the system have been provided. System controls are done with a two layer block model on Simulink. Simulink is able to control actuators via our main controllers Arduino Mega 2560 at external mode. System's closed loop control has been done with well known Proportional-Integral-Derivative (PID) controller. The completed prototype has been tested in target and tracking modes. Test results are provided in the thesis.
EFFECTS OF ACTIVE LANDING GEAR ON THE ATTITUDE DYNAMICS OF A QUADROTOR
(2015-10-11) YILDIZ, Mehmet; ARIKAN, Kutluk Bilge; İRFANOĞLU, Bülent
In this thesis, effects of the active landing gears which are used in most of the commercial multirotor systems, on attitude dynamics are investigated. Utilization for the purpose of stability assistance, steering and the agility enhancement is discussed. A Quadrotor test system is constructed by using a commercial quadrotor frame, actuators, drivers and an open source embedded flight controller. The Quadrotor system with active landing gears is modelled on Matlab/Simulink environment. PID controller which is used in the embedded flight controller is designed to control attitude dynamics. PID controller is tuned on the test bench and tuned parameters are applied to the identified model of the Quadrotor. This model is used to optimize the controller parameters. For the active landing gear system, a simple servo motor actuated mechanism is used and this mechanism is applied on the Quadrotor roll axis. The positions of the gears are controlled by embedded flight controller as well. Experiments show that active landing gears can be used to improve the stability, to steer platform in horizontal plane and to improve the agility by applying an additional moment about the roll axis.
HYBRID ELECTROENCEPHALOGRAM (EEG) – FUNCTIONAL NEAR INFRARED SPECTROSCOPY (FNIRS) BRAIN-COMPUTER INTERFACE (BCI) CLASSIFICATION OF MOTOR IMAGERY TASKS
(2022-01-26) Hasan, Mustafa; Khan, M. Umer
Hybrid Brain Computer Interface, a combination of two or more neurophysiological signals, is getting attention for its ability to complement a single modality drawbacks and in achieving reliable results by extracting harmonizing features. A hybrid EEG fNIRS BCI system achieved through the fusion of simultaneously recorded functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) signals, is used to overcome the limitations of uni-modality and to achieve high motor tasks classification. Although, hybrid BCI approach enhanced the performance of the system, yet the improvements are still modest because of the lack of computational methods to fuse the two modalities. The contributions of this thesis is twofold: a novel channel selection correlation coefficient approach to select the most representative channels and a novel fusion approach using Multi-resolution singular value decomposition (MSVD). MSVD is utilized to achieve both system-based and feature based fusion for the optimal EEG-fNIRS channels. Another contribution of this thesis is to utilize canonical correlation analysis (CCA) for feature-based fusion. Correlation analysis is used primarily to study the relationship between the two modalities. CCA feature-based fusion improved performance through maximizing the inter-subject covariance across the two modalities. Through simulation results, it can be witnessed that the proposed approaches help to achieve optimal performance while reducing the computational complexity.
RECIPROCAL ALTRUISM BASED PATH PLANNING USING PARTICLE SWARM OPTIMIZATION (PSO)
(2022-01-26) Maeedi, Ali Fadhil Ali; Khan, M. Umer
Encountering the problems of nature that has always been a challenging task, what makes it more difficult is the change in operating conditions over time. Therefore, a robust algorithm is needed that is able to track the continuously changing optima over time. In this thesis, a novel particle swarm optimization based population kinship connectivity is proposed with the intent to improve the performance by introducing the sharing of particles information. The proposed algorithm, Reciprocal Altruism based Particle Swarm Optimization, utilizes the kinship relatedness between particles during the optimization process to reciprocate the significant data regarding the environment. Reciprocal altruism theory is regularly conjured to clarify why irrelative particles helped as pairs in different types of intra-group cooperative conduct, e.g., egg exchanging among hermaphroditic fishes, blood spewing forth among vampire bats, assessment of predator among sticklebacks, allogrooming among vervet monkeys and impala, sustenance share among humans, brown capuchin monkeys, and basic chimpanzees. Utilizing the concept of reciprocation, the RAPSO will ensure that all particles remain in close contact with each other through information exchange. Moreover, the amount of information that is exchanged between the particles is dependent upon their physical placement in the search space regions. Depending upon their region, they can be either classified as a donor or a recipient; furthermore, the amount of information exchanged between the particles is directly monitored through their associated health indicator. The performance of the proposed approach shows that the reciprocal sharing has played its role effectively in order to control the movement of the swarm along the optimized path. The simulation results proved that RAPSO outperforms the conical PSO algorithm both in terms of error reduction and close connectivity.
DESIGN OF CONTROL SYSTEMS FOR AN AERIAL MANIPULATOR
(2022-01-26) Başaranoğlu, Ahmet Turgut; Khan, Muhammad Umer; Arıkan, Kutluk Bilge
Within the scope of this thesis, attitude and position control systems are designed and discussed for an aerial manipulator which is composed of a quadcopter and a single degree of freedom robotic arm. The arm is working in the pitch plane of the aerial manipulator. Several control schemes exist to control its movements, but, most of them have been tested only under simulation scenarios. The comprehensive system dynamics (i.e. the coupled quadcopter and manipulator dynamics) is controlled by the centralized control architecture. In addition, the decentralized control approach is applied by designing separate control systems for the quadcopter and the arm. The use of the arm for the purposes of disturbance rejection, regulation, agility enhancement, and the steering are discussed in the scenarios. The Active Disturbance Rejection Control (ADRC), Tracking type Linear Quadratic Regulator (LQR), and the Cascaded PID control algorithms are designed. The selected control architecture is applied on an aerial manipulator that is working indoor for the selected scenario. Ultra-wideband localization system is used to measure the position and altitude of the system. The designed control system is implemented in real-time using Raspberry Pi 3 B +, Phyton script and Matlab/Simulink. A test bench is used to tune the parameters of the attitude controller. Then, basic flight tests are utilized to tune the altitude and position controllers. The simulations and tests show that the manipulator assists the aerial manipulator to reject the disturbances, control the attitude dynamics, and to steer the system.
AN EFFECTIVE PATH PLANNING ALGORITHM FOR SWARM OF ROBOTS IN AN UN-KNOWN ENVIRONMENT
(2022-01-25) Abdi, Mohammed Isam Ismael; Khan, Umer
In many circumstances, several mobile robots —independent agents— team up to achieve goals that are hard or impossible for an individual robot. These mobile robots cooperate to perform any particular task, complexity of this cooperation is correlated with the swarm size. Each individual robot is to interact with the local environment using sensors. The primary concern for the swarm is to define and follow a safe route from initial to target location. To achieve this task, many algorithms exist in the literature, namely, Neural Network, Genetic Algorithms, Bacterial Foraging Optimization, Ant Colony Optimization, Artificial Potential Field etc. Among these, Bacterial Foraging Optimization (BFO) algorithm has attracted the attention of many scientists due to its effectiveness of finding the destination with the consideration of all known obstacles in the work space ensuring safety. Furthermore, it discovers and always follows the determined path correctly. BFO is a straightforward but strong bioinspired method of optimization using the analogy of swarming principles and social behavior in nature. The BFO successfully searches for an optimal path from start to goal point in the presence of obstacles over a flat surface map. However, the algorithm suffers from getting stuck in local minima whenever non-convex obstacles are encountered. In case of any of these robots from the swarm getting stuck is considered as the failure of the whole task. This research proposes an improved version of BFO algorithm that can effectively avoid obstacles, both of convex and non-convex nature. The proposed algorithm helps the robot to recover from local minima by covering a certain distance in an opposite direction to the obstacle. The algorithm will start generating virtual obstacles to generate a safe path when facing acute angle. This information is then passed onto other robots, so that they can also avoid local minima. To test the effectiveness of the proposed algorithm, a comparison is made against the existing BFO algorithm. The performance of both algorithms is tested in an unknown dynamic and static environments. Through results, it is witnessed that the proposed approach successfully recovers from the local minima, whereas, BFO gets stuck.
ENSURING STABILITY OF A QUADROTOR FOR PROPELLER FAILURE
(2022-01-14) Altınuç, Kemal Orçun; KHAN, Muhammad Umer
In this thesis, a novel solution is presented for a fixed-wing quad-rotor to maintain its position in 3D space, despite losing one or two–opposite– propellers by sacrific ing the yaw motion. According to the proposed solution, quad-rotor spins about a primary axis, fixed with respect to the vehicle and changes this axis for translational movement. A multi-loop cascaded control law is used in order to stabilize the attitude and the position of the quad-rotor for propeller failures. First, equilibrium solutions for motor failure scenarios are calculated. Then, a reduced attitude controller and position controller is designed around the linearized system for a reference and a custom quadrotor. Simulations are performed on Matlab/Simulink and Matlab/Simscape and results are compared. Lastly, CAD drawings of a custom quadrotor is used to estimate the moment of inertia of the quadrotor and results are verified with the Bifilar Pendulum Experiment. The results show that quadrotor sta bility has been achieved for propeller failure.
DEVELOPMENT OF BEHAVIORAL MODULES FOR SOCIAL ROBOT PRODUCT FAMILIES
(2022-01-14) ÖZER, İlayda; ERDEN, Zühal
In this thesis, behavioral modules for social robots (SoBOTs) are developed by using the 3D Design Structure Matrix (DSM) model. Behavioral modules are the building blocks for systematic design of social robot families, composed of personalized social robots to satisfy diverse needs of individuals or small groups. The 3D DSM is independent of any physical solution principle and is based on 3 different behavioral elements of robots, namely "perception", "cognition" and "motoric action". In this thesis, data for these elements are extracted from 45 different social robots existing in the literature. Sixteen behavioral modules are developed by defining the mutual interactions between these three types of behavioral elements of social robots. Among them, six sample modules are designed and manufactured in the laboratory. A model social robot family of two robots, which uses different combinations of these 6 modules is developed for technology demonstration.
STATE OF CHARGE (SOC) OPTIMIZATION OF RECONFIGURABLE BATTERY NETWORK
(2024-05-01) ATAR, ZAINAB; Khan, Umer
Batteries are a major source of energy, especially lithium-ion (Li-ion). Their astounding chemical properties have made them favourites for many applications areas including electric vehicles (EVs). To meet the system requirements, multiple batteries are connected in a fixed or a reconfigurable structure. Given the many problems faced by these architectures especially the fixed structure, including exceeding the use of the weak battery, this study proposes an advanced battery system that can be reconfigured to meet all system requirements. In addition to its ability to bypass the use of a damaged battery, a battery that is charging can be completely separated from the rest of the connection. These batteries, when connected in a specific configuration, whether series, parallel or hybrid, face a performance defect due to the repeated use that causes the imbalance in charging and discharging among the batteries. If one of the batteries is damaged due to the overcharging or over-discharging, it may lead to bad effects on the overall performance of the system. This research proposes an advanced battery management system to maintain a balance among batteries to improve their lifecycle. It also prevents overcharging or over-discharging of batteries by providing the maximum value for charging or the minimum value for discharging, as at these two values the state of the battery is reversed from discharge to charging or vice versa. Thus, keeping the system working at the highest level throughout the run time. This study also proposes an optimization algorithm to supply the optimal load voltage. The choice of this configuration depends on the required voltage as well as the state of charge (SOC) for each battery. To keep the system equipped with the required voltage throughout the runtime, this thesis proposes an algorithm to replace the low-charge battery with another battery ready to discharge in series and parallel configurations. Moreover, in the hybrid configuration, the common battery forming the bridge between two configurations is also replaced. Given that all batteries are charging, this research suggests supplying the load with voltage from an external voltage source until at least one battery becomes available. The results based on the use of simulation in the MATLAB showed the ability of the proposed algorithms to achieve an effective battery management system that protects all batteries from overcharging and over discharging. Additionally, it is also demonstrated that the system is capable of providing the required voltage throughout the run time despite the changes in the configuration. It also shows the ability of the Improved Reconfigurable Energy Enhanced Architecture (I-REEA) to meet all changes in the connections during the run time.

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