Yazar "Okumus, Fatih" seçeneğine göre listele

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    Cloud Based Indoor Navigation for ROS-enabled Automated Guided Vehicles
    (Ieee, 2019) Okumus, Fatih; Kocamaz, Adnan Fatih
    In Cyber-Physical Systems, logistical activities with automatic guided vehicles (AGV) are indispensable for Industry 4.0 integration. In order to navigate the AGVs to be used in logistics, difficulties such as localization of AGV, mapping the environment, mobile-immobile obstacle avoidance, and optimum task allocation must be overcome. All these operations can be realized with an architecture that provides communication infrastructure and management mechanism in multiple robots. In this publication, cloud-based, ROS-enabled communication and navigation methods for multiple AGVs are proposed. The proposed method was tested and applied successfully in a laboratory environment.
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    A Cloudware Architecture for Collaboration of Multiple AGVs in Indoor Logistics: Case Study in Fabric Manufacturing Enterprises
    (Mdpi, 2020) Okumus, Fatih; Donmez, Emrah; Kocamaz, Adnan Fatih
    In Industry 4.0 compatible workshops, the demand for Automated Guided Vehicles (AGVs) used in indoor logistics systems has increased remarkably. In these indoor logistics systems, it may be necessary to execute multiple transport tasks simultaneously using multiple AGVs. However, some challenges require special solutions for AGVs to be used in industrial autonomous transportation. These challenges can be addressed under four main headings: positioning, optimum path planning, collision avoidance and optimum task allocation. The solutions produced for these challenges may require special studies that vary depending on the type of tasks and the working environment in which AGVs are used. This study focuses on the problem of automated indoor logistics carried out in the simultaneous production of textile finishing enterprises. In the study, a centralized cloud system that enables multiple AGVs to work in collaboration has been developed. The finishing enterprise of a denim manufacturing factory was handled as a case study and modelling of mapping-planning processes was carried out using the developed cloud system. In the cloud system, RestFul APIs, for mapping the environment, and WebSocket methods, to track the locations of AGVs, have been developed. A collaboration module in harmony with the working model has been developed for AGVs to be used for fabric transportation. The collaboration module consists of task definition, battery management-optimization, selection of the most suitable batch trolleys (provides mobility of fabrics for the finishing mills), optimum task distribution and collision avoidance stages. In the collaboration module, all the finishing processes until the product arrives the delivery point are defined as tasks. A task allocation algorithm has been developed for the optimum performance of these tasks. The multi-fitness function that optimizes the total path of the AGVs, the elapsed time and the energy spent while performing the tasks have been determined. An assignment matrix based on K nearest neighbor (k-NN) and permutation possibilities was created for the optimal task allocation, and the most appropriate row was selected according to the optimal path totals of each row in the matrix. The D* Lite algorithm has been used to calculate the optimum path between AGVs and goals by avoiding static obstacles. By developing simulation software, the problem model was adapted and the operation of the cloud system was tested. Simulation results showed that the developed cloud system was successfully implemented. Although the developed cloud system has been applied as a case study in fabric finishing workshops with a complex structure, it can be used in different sectors as its logistic processes are similar.
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    Comparing Path Planning Algorithms for Multiple Mobile Robots
    (Ieee, 2018) Okumus, Fatih; Kocamaz, Adnan Fatih
    The use of mobile robots in industrial applications is increasing day by day. As a result of this increase, efficiency in the use of mobile robots has also become important. In particular, path planning is a significant area of research to improve efficiency in mobile robot navigation. In path planning, it is aimed to find optimum and obstacle free paths to the starting and ending points to fulfill multiple tasks. In this paper, A *, D * and PSO algorithms, frequently used to optimize the path multiple robots reach targets in an environment with obstacles, have been compared. In addition, a mobile robot simulation software has been developed to measure the performance of algorithms. At the end of the study, the performance of the algorithms was showed by measuring the path lengths and the process time of algorithms.
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    Detection and Counting of Oncorhynchus Mykiss Spermatozoa
    (Ieee, 2015) Okumus, Fatih; Kocamaz, Adnan Fatih; Ozgur, Mustafa Erkan
    Today in the world, a large portion of the trout species grown in the fisheries constitutes Oncorhynchus Mykiss. In order to increase the efficiency of Oncorhynchus Mykiss's production, it is expected to be in fair value of its sperm quality parameters for fertilize. Investigation by examination under a microscope with the conventional method of quality parameters is the waste of time for researchers. In this work, we present a system that can detect the cell concentration, which is an important quality parameter for the fish spermatozoa, with Otsu Threshold and Connected Component Labeling methods.
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    Exploring the Feasibility of a Multifunctional Software Platform for Cloud Robotics
    (Ieee, 2018) Okumus, Fatih; Kocamaz, Adnan Fatih
    Strengthening the infrastructure of the Internet has made global data access easier and so cloud computing is at the forefront. Cloud technologies are used in the many work area, because they provide big data storage capacity, low computational costs and scalable data management. Cloud robotics, a special form of cloud computing, manages mobile robots with the advantages mentioned above, as well as providing a telepathic agreement mechanism among the robots. This work presents the development of a software platform for managing cloud-based operations such as simultaneous localization and mapping (SLAM), path planning and optimum task distribution for mobile robots. Demonstration software has also been implemented in the study, which provides a simulation environment that allows testing of the developed system. At the end of the study, the cloud software was tested with the demonstration application and the test results were shown.
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    The in vitro toxicity analysis of titanium dioxide (TiO2) nanoparticles on kinematics and biochemical quality of rainbow trout sperm cells
    (Elsevier Science Bv, 2018) Ozgur, Mustafa Erkan; Balcioglu, Sevgi; Ulu, Ahmet; Ozcan, Imren; Okumus, Fatih; Koytepe, Suleyman; Ates, Burhan
    In recent years, titanium dioxide (TiO2) nanoparticles (NPs) as metal oxide nanoparticles are widely used in industry, agriculture, personal care products, cosmetics, sun protection and toothpaste, electronics, foodstuffs and food packaging. This use of nano-TiO2 has been associated with environmental toxicity concerns. Therefore, the aim of this study was to evaluate the in vitro effect of different doses of TiO2 NPs (similar to 30-40 nm) (0.01, 0.1, 0.5, 1, 10 and 50 mg/L) at 4oC for 3 h on the sperm cell kinematics as velocities of Rainbow trout (Oncorhynchus mykiss, Walbaum, 1792) sperm cells. Furthermore, oxidative stress markers (total glutathione (TGSH) and superoxide dismutase (SOD) were assessed in sperm cells after exposure to TiO2 NPs. According to the obtained results, there were statistically significant (P < 0.05) decreasing in the velocities of sperm cells after 10 mg/L TiO2 NPs and an increase the activity of SOD (P < 0.05) and TGSH levels were determined.
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    Load Flow Optimization of 154 kV Malatya Transmission Line Using Differential Evolution Algorithm
    (Ieee, 2017) Akdag, Ozan; Karadogan, Ismail; Okumus, Fatih; Yeroglu, Celaleddin; Karci, Ali
    Amplitude, phase angle, active and reactive powers flowing in each busbar of a power system can be seen by performing a load flow analysis. From these data, it is possible to determine the voltage drop, the distribution of the forces, the loading of the equipment and the losses of the related power system. Then, Active power losses can be reduced by making improvements at the points where losses are present in the power system. Power losses can be reduced by reactive power compensation considerably. In this study, Differential Evolution (DE) algorithm is used to determine the values of the capacitor groups to be added to the corresponding busbar to reduce the losses of 154 kV transmission system. The optimum load flow is ensured by optimizing a transmission system with the developed algorithm.