Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Inertial Measurement Units for Motion Control of Surgical Endoscopic Robot(Izmir Institute of Technology, 2018) Erat, Sercan; Özdemirel, BarbarosInertial measurement units (IMUs) are preferable over other electromechanical user interfaces for robotics applications that require hands-free operation. In case of a surgical endoscopic robot, one of the requirements is a user interface that gives the surgeon ability to control the camera position while holding other surgical tools. An IMU used for this purpose should provide precise position information in a small motion range restricted by a few degrees of rotation. In this study, major difficulties in establishing a user interface between an IMU and a surgical robotic arm are identified, and the necessary solutions for implementation of such an interface are presented. The study focuses on the IMU devices that combine accelerometers and gyroscopes based on micro-electromechanical systems (MEMS) technology because of their smaller size and low power requirement. Working principles and the calibration techniques of MEMS IMUs are reviewed. Three fusion algorithms that combine accelerometer and gyroscope data to determine the orientation of an object in three-dimensional space are implemented. Performance of these fusion algorithms and critical specifications of MEMS IMUs from three different manufacturers are evaluated by monitoring sensor data through a wireless interface. A graphical evaluation software was developed to test position mapping methods by steering field of view of a hypothetical camera towards randomly determined targets on the computer screen. Effectiveness of the position mapping methods was evaluated by several users by comparing the total angular displacement and the elapsed time required to reach a number of simulated targets.Master Thesis Accelerometer Based Handwritten Character Recognition Using Dynamic Time Warping(Izmir Institute of Technology, 2016) Tunçer, Esra; Ünlü, Mehmet ZübeyirCharacter and gesture recognition are one of the most studied topics in recent years. Character recognition studies are generally based on image processing. Only a few studies can be found about character recognition as gesture recognition. Gesture recognition is making the computers understand human body movements by using different kind of knowledge of the environment. This knowledge can be obtained by image or sensor-based efforts. Accelerometer is the most used sensor in gesture recognition, so in this study a 3-axis accelerometer is used. In this thesis, English alphabet‟s lowercase characters are used. A ring-like device which contains accelerometer in it is used. After obtaining the acceleration data of each character with 20 repetitions, we apply filtering, segmentation and normalization preprocessing steps for each signal. Since there are different accelerations and decelerations between each repetitions, Dynamic Time Warping (DTW) algorithm has been chosen to determine the similarities between signals. DTW is an algorithm that uses the amplitude values of the signals, so it is weak to amplitudes that shift in time domain. To overcome this shortcoming, the method called Derivative Dynamic Time Warping (DDTW) has been applied to the acceleration signals. DTW and DDTW methods have been compared and we have found that even we remove the normalization step; DDTW gives better results than DTW. By comparison of linear alignment and DTW, the results show that DTW gives better recognition rates for signals with different accelerations and decelerations. DTW also gives better result for the different length signals.