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Kağıt Tabanlı Magnetoforetik Sensör Geliştirilmesi
(Abdullah Gül Üniversitesi Fen Bilimleri Enstitüsü, 2022) FAROOQI, MUHAMMAD FUAD; Farooqi, Muhammad Fuad; İçöz, Kutay
One of the widely used type of biosensors are paper-based lateral flow systems. They are used to detect a wide variety of biomolecules like microorganisms, proteins, chemicals, oligonucleotides among many others. In this research, a setup was created using dual magnet sets in which the flow of cell sample on two kinds of different sample paper was explored. There were two factors which affected the movement of the sample the most, the magnetic field and the wetting. Images were obtained using a cell phone along and/or a bright field optical microscope and then analyzed using image processing. Images were also taken using scanning electron microscope. The effects of the wetting and the magnetic field were tested and studied. It was found that at least 90% of the cells were able to reach the edge of the paper. Although the cells were not able to maintain their shape on the paper due to the unideal conditions of the paper for cells but still this kind of paper-based lateral flow assay setup can be used for cells to see their behavior when they were labelled and exposed to a magnetic field. This research shows support that this technique can be used for separating cells as well as detecting different cells.
Hava-Yer Robot Ekipleri için Bağıl Lokalizasyon ve Koordinasyon
(Abdullah Gül Üniversitesi Fen Bilimleri Enstitüsü, 2021) Yıldırım, İsa Emre; Yıldırım, İsa Emre; Güler, Samet
Recently, autonomous robot teams have been implemented broadly in many social and military applications such as firefighting, agriculture, search and rescue, mapping, target tracking, and docking. A mix of different types of ground robots and aerial vehicles can be employed in a robot team to accomplish tasks efficiently and robustly. Such heterogeneous systems show unparalleled benefits in complex tasks compared to teams composed of identical robot types. In a heterogeneous robot team, precise relative localization, i.e., estimating a robot's position with respect to its neighbor robots, plays a key role. We develop a relative localization system for air-ground robot teams where an aerial vehicle and multiple ground robots work in coordination to perform a reliable relative position estimation. The aerial vehicle is employed to detect special patterns on the ground robots by an onboard monocular camera, while the ground robots perform relative position estimation based on inter-robot distances acquired by ultrawideband sensors and the bearing and heading angles received from the aerial vehicle by communication. Thus, the aerial vehicle serves as an absolute frame provider for the entire team. Notably, each robot in the team uses onboard communication and computation capabilities solely without any need for an external localization infrastructure, making the team realizable in all conditions including GNSS-denied environments. We propose a multi-rate extended Kalman filter algorithm to handle different data rates of the sensor measurements. We carried out an extensive simulation study with a drone and five ground robots in a leader-first follower formation. Simulation results showed a successful estimation performance with an error rate of up to five centimeters in the relative position estimations in both axes. Keywords: Relative localization, Heterogeneous multi-robot systems, estimation algorithms, ultrawideband sensors

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