Master Degree / Yüksek Lisans Tezleri

Permanent URI for this collectionhttps://hdl.handle.net/11147/3008

Browse

Filters

2004 - 200912010 - 201922020 - 20242

Settings

Scopus Q: search.filters.scopusQuartile.N/ASubject: search.filters.subject.Robotics

Search Results

Now showing 1 - 5 of 5
  • Master Thesis
    Evaluating Adoption Factors for Robotic-Assisted Surgery With the Analytical Hierarchical Process
    (01. Izmir Institute of Technology, 2024) Sarıgöl, Işın Sözen; Dindaroğlu, Burak; Başoğlu, Ahmet Nuri
    The objective of this master's dissertation is to evaluate adoption factors for robotic-assisted surgery (RAS) using the Analytical Hierarchy Process (AHP) as its evaluation methodology. Robotic-assisted surgery is used in various surgical fields. It is mainly used as a tool in numerous disciplines' minimally invasive surgery procedures (MIS). Since it has so many different application areas and actors, the determination of its adoption factors and evaluation process of these factors' priorities for surgeons is a highly complex issue that includes multicriteria of decision-making and numerous surgeons. A comprehensive list of these possible adoption factors recognized by conducting an extensive literature review, was picked and chosen. First, we had 310 factors mentioned in the literature that have a potential impact on the adoption process of the RAS. We have reduced these to 20 factors that are categorized under five different main criteria. By this, a unique AHP tree that is this thesis' contribution to the literature was developed. The research data was collected by an online survey from the surgeons of various disciplines working in Türkiye. Our final sample to evaluate priorities consisted of forty-one surgeon responses in total. The evaluation process consists of three steps: analyzing individual-based pairwise comparison matrices, their consistency rations, and their priority vectors. We executed the same workflow for the aggregated analysis for disciplined-based and all aggregation. Results are examined in detail and concluded with insightful interpretations.
  • Master Thesis
    Learning of Tasks With Robot Programming by Demonstration
    (Izmir Institute of Technology, 2022) Argüz, Serdar Hakan; Altun, Kerem; Ertuğrul, Şeniz
    Increasingly more unstructured environments of today’s industry challenge the robots to have the capability to dynamically adapt to variations in the part sizes and positions. Traditional programming methods fall short of answering such needs. Programming by demonstration is an approach that allows the robots to learn tasks from human demonstrations. Improvements in the generalization of individual tasks that compose the complex assembly operations are an indispensable need for a more extensive adoption of PbD in the industry. This thesis aims to improve the generalization of the peg-in-hole task against variations in the hole positions. It uses the change in the hole position a metric for the novelty of the task and tests the success rate at increasing distances. The relationship between the novelty of the task and its success is examined for two different learning strategies. In the first strategy, only the positional characteristics of the task are learned, whereas both positional and force characteristics are learned in the latter. It is found that the success rate of the task decreases in both cases as the distance increases. However, the hybrid position/force learning strategy outperforms the purely positional one at all distances. As a result, this strategy is experimentally shown to be a valid approach to improve the generalization of the peg-in-hole task for changing hole positions. Incorporation of this strategy with existing frameworks and orientation generalization methods is suggested as future work.
  • Master Thesis
    On Improving the Performance of Repetitive Leaning Controllers
    (Izmir Institute of Technology, 2019) Çobanoğlu, Necati; Tatlıcıoğlu, Enver
    Robot manipulators are widely used to perform pre–defined tasks repetitively. Nearly all of the mass production factories use the robot manipulators to perform specific operations over and over again. In such a system, the control design may contain some difficulties, unavailabilities and/or there would be additive disturbances due to the periodic motion. Moreover, cost reduction may be vital, hence sensor usage has to be reduced. In the first part of this thesis, to address those restrictions, a model free full state feedback repetitive learning controller which is fused with a one–layer neural network is proposed for robot manipulator which performs a periodic motion. Stability of the system is ensured via Lyapunov based techniques. Numerical simulations and experimental results are introduced to demonstrate the performance of the proposed controller. In the second part of the thesis, under the additional constraint that velocity measurements being unavailable, output feedback repetitive learning controller fused with a neural network term is investigated. The dynamic model of the robot manipulator is again considered as uncertain to avoid its usage as part of the control design, and the reference position vector is still considered to be periodic. The stability of the closed loop system is investigated via Lyapunov based techniques. Numerical simulations are added to demonstrate the proposed controller performance.
  • Master Thesis
    Position / Force Control of Systems Subjected To Communicaton Delays and Interruptions in Bilateral Teleoperation
    (Izmir Institute of Technology, 2012) Uzunoğlu, Emre; Dede, Mehmet İsmet Can
    Teleoperation technology allows to remotely operate robotic (slave) systems located in hazardous, risky and distant environments. The human operator sends commands through the controller (master) system to execute the tasks from a distance. The operator is provided with necessary (visual, audio or haptic) feedback to accomplish the mission remotely. In bilateral teleoperation, continuous feedback from the remote environment is generated. Thus, the operator can handle the task as if the operator is in the remote environment relying on the relevant feedback. Since teleoperation deals with systems controlled from a distance, time delays and package losses in transmission of information are present. These communication failures affect the human perception and system stability, and thus, the ability of operator to handle the task successfully. The objective of this thesis is to investigate and develop a control algorithm, which utilizes model mediated teleoperation integrating parallel position/force controllers, to compensate for the instability issues and excessive forcing applied to the environment arising from communication failures. Model mediation technique is extended for three-degrees-of-freedom teleoperation and a parallel position/force controller, impedance controller, is integrated in the control algorithm. The proposed control method is experimentally tested by using Matlab Simulink blocksets for real-time experimentation in which haptic desktop devices, Novint Falcon and Phantom Desktop are configured as master and slave subsystems of the bilateral teleoperation. The results of these tests indicate that the stability and passivity of proposed bilateral teleoperation systems are preserved during constant and variable time delays and data losses while the position and force tracking test results provide acceptable performance with bounded errors.
  • Master Thesis
    Design of a Mars Rover Suspension Mechanism
    (Izmir Institute of Technology, 2004) Barlas, Fırat; Alizade, Rasim
    It is obvious that rovers are important vehicles of today.s solar system exploration. Most of the rover designs have been developed for Mars and Moon surface in order to understand the geological history of the soil and rocks. Exploration operations need high speed and long distance traversal in a short mission period due to environmental effects, climate and communication restrictions. Several mechanisms have been suggested in recent years for suspensions of rovers on rough terrain. Although their different mechanisms have found a widespread usage in mobile robotics, their low operation speed is still a challenging problem. In this research, a new suspension mechanism has been designed and its kinematic analysis results were discussed. Standard rocker-bogie suspension mechanism, which has been developed in the late 1990.s, has excellent weight distribution for different positions on rough terrain. New design, mostly similar to rocker-bogie suspension system, has a natural advantage with linear bogie motion which protects the whole system from getting rollover during high speed operations. This improvement increases the reliability of structure on field operations and also enables the higher speed exploration with same obstacle height capacity as rocker-bogie. In this thesis study, new bogie mechanism consisted of double-lambda mechanisms, which has been firstly presented by Pafnuty Lvovich Chebyshev in 1869, is solved by analytically to define the positions and singular configurations. A new structural synthesis formula also has been introduced for such suspension mechanisms with lower and higher kinematic pairs. By using structural synthesis methods, a suspension mechanism has been designed with double-lambda mechanism. Equivalent force and moment functions were also derived with equation of motion method. The results are confirmed with the computer analysis made by Visual Nastran 4D®. For this purpose, a computer model has been constructed and assembled with the same design parameters of NASA Mars Exploration Rovers (MER1 and MER2).