Phd Degree / Doktora

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Design of a Robot Assisted Minimally Invasive Surgical System for Pituitary Tumor Surgery Based on Safety Features
(Izmir Institute of Technology, 2020) Maaroof, Omar Waleed Najm; Dede, Mehmet İsmet Can
The study is on the designing a robot assisted endonasal endoscopic surgical system; NeuRoboScope, the pituitary tumor resection surgery system. This system comprises a passive and an active arm. The passive arm positions the active arm in the surgery zone while the active arm assists the surgeon by positioning the endoscope during the surgery. The focus of this thesis is the mechanical and control safety features that can be implemented in the system. The safety enhancement methods of robot assisted minimally invasive surgery systems are investigated. Among the seventeen robot assisted endoscope holders, sixteen of them have been implemented in pituitary tumor and sinus surgeries. Safety is the main criterion that advances the progress of these systems and places them in operation rooms. Accordingly, two optimization procedures have been applied during the design of the NeuRoboScope system that have a direct effect on the suggested safety features. A novel optimization technique is proposed by employing a redundancy resolution method. The most suitable fixing point of the passive arm and its first link length is optimized to achieve the maximum manipulability with restrictions imposed by a modified condition number index and impedance of the passive arm. The active arm's partial gravity compensation is studied. Three spiral springs are used as counter-springs as the most compact and lightweight partial gravity compensation method. Particle swarm optimization method is employed for the optimization of the design parameters: spiral spring stiffnesses and preload angles. Consequently, at least 66% of actuator loads are compensated.
Macro-micro robotic manipulation: A laser cutting case study
(Izmir Institute of Technology, 2019) Uzunoğlu, Emre; Dede, Mehmet İsmet Can; Kiper, Gökhan
This dissertation focuses on investigation and devising of proper methodology to utilize a special type of kinematic redundancy, namely macro–micro manipulation, in the scope of robotic science. Briefly, macro-micro manipulation is comprised of two kinematically different mechanisms that have distinct characteristics, which work on macro and micro-scale. Aim of this dissertation is to present the most convenient motion planning and control algorithm to resolve kinematic redundancy for macro-micro manipulation concept. Controller designs, including the motion planning algorithms are devised taking into account the selected industrial case study. Additionally, a general framework controller is developed for macro-micro manipulation. Experiments with industrial setup and simulation verifications are done for the proposed methodologies. It is proven with simulation test results and experiments that the task completion duration for a laser cutting machine is reduced by enhancing the acceleration capability with the macro-micro manipulation. Although the proposed methodologies are implemented for a specific case, it can also be used for other systems considering the versatility of the proposed methodology. The core novelty of this research is the introduction of methodologies in order to achieve the maximum efficiency for the combined use of macro and micro-scaled manipulators. As an outcome of this study, a redundant laser cutting machine that can move with higher accelerations by making use of macro-micro manipulation is developed as a first of its kind in the Turkish machine industry and third of its kind in the world.

Phd Degree / Doktora

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