My research interests lie in robotic manipulation, magnetic navigation systems, control systems, and healthcare robotics. During my Ph.D. at Aalto University, I worked with the Intelligent Robotics research group led by Prof. Ville Kyrki and the Robotics Instruments group led by Prof. Quan Zhou. My work focused on developing robotic systems and autonomous solutions for medical applications.
I enjoy building intelligent systems that can address real world challenges. I have hands on experience with Python, Matlab/Simulink, and C++, and I am passionate about advancing robotics technologies that can create meaningful impact in healthcare.
I’m thrilled to share my projects and contributions with you here on my portfolio. Feel free to reach out.
Robotic magnetic manipulation offers a minimally invasive approach to gastrointestinal examinations through capsule endoscopy. However, controlling such systems using external permanent magnets (EPM) is challenging due to nonlinear magnetic interactions, especially when there are complex navigation requirements such as avoidance of sensitive tissues. In this work, we present a novel trajectory planning and control method incorporating dynamics and navigation requirements, using a single EPM fixed to a robotic arm to manipulate an internal permanent magnet (IPM). Our approach employs a constrained iterative linear quadratic regulator that considers the dynamics of the IPM to generate optimal trajectories for both the EPM and IPM. Extensive simulations and real-world experiments, motivated by capsule endoscopy operations, demonstrate the robustness of the method, showcasing resilience to external disturbances and precise control under varying conditions. The experimental results show that the IPM reaches the goal position with a maximum mean error of 0.18 cm and a standard deviation of 0.21 cm. This work introduces a unified framework for constrained trajectory optimization in magnetic manipulation, directly incorporating both the IPM’s dynamics and the EPM’s manipulability.
@article{isitman2025trajectory,title={Trajectory Planning and Control for Robotic Manipulation of Magnetic Capsules},author={Isitman, Ogulcan and Alcan, Gokhan and Kyrki, Ville},journal={IEEE Robotics and Automation Letters},year={2025},publisher={IEEE},dimensions={true},}
Probing Early Particle-Cell Membrane Interactions via Single-Cell and Single-Particle Interaction Analysis
Houari Bettahar, Christos Tapeinos, Oğulcan Işıtman, and 4 more authors
Endocytosis is vital for nutrient uptake and nanomedicine applications, but the biophysics of the pre-internalization phase remains poorly understood at single-cell level. This study uses advanced robotic techniques to analyze pre-internalization adhesion mechanics. MiaPaCa-2 cells, pancreatic cancer, displayed three interaction phases: rapid lateral displacement, a quasi-plateau phase, and linear displacement during extraction. Adhesion time is linked to changes in cell mechanics, with MiaPaCa-2 cells displaying a biphasic uptake process—an initial rapid adhesion phase followed by a strengthening of adhesion high variability in viscoelasticity. In contrast, fibroblasts show a gradual increase in adhesion forces, accompanied by significant rises in stiffness and viscosity. Unlike traditional endocytosis studies, this study focuses on how pathway inhibitors alter initial membrane engagement rather than uptake mechanisms. Clathrin inhibition increased adhesion by 39%, caveolae inhibition by 27%, and microtubule inhibition reduced adhesion by 48%, indicating microtubules’ role in adhesion dynamics. Combined inhibition of clathrin, caveolae, and microtubules reduced adhesion by 70%, showing that disrupting multiple pathways severely impairs particle adhesion. Under repeated stress, MiaPaCa-2 cells soften (≈75% Young’s modulus reduction) due to cytoskeletal disruption, while fibroblasts gradually soften (≈71% modulus reduction), highlighting cellular adaptations. These findings provide new insights into the pre-internalization of particles at the single-cell level.
@article{bettahar2025probing,title={Probing Early Particle-Cell Membrane Interactions via Single-Cell and Single-Particle Interaction Analysis},author={Bettahar, Houari and Tapeinos, Christos and I{\c{s}}{\i}tman, O{\u{g}}ulcan and D'Amico, Carmine and Correia, Alexandra and Santos, H{\'e}lder A and Zhou, Quan},journal={Advanced Functional Materials},pages={2507301},year={2025},publisher={Wiley Online Library},dimensions={true},}
2022
Simultaneous and Independent Micromanipulation of Two Identical Particles with Robotic Electromagnetic Needles
Ogulcan Isitman, Hakan Kandemir, Gokhan Alcan, and 2 more authors
In 2022 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), 2022
Magnetic manipulation of particles at close vicinity is a challenging task. In this paper, we propose simultaneous and independent manipulation of two identical particles at close vicinity using two mobile robotic electromagnetic needles. We developed a neural network that can predict the magnetic flux density gradient for any given needle positions. Using the neural network, we developed a control algorithm to solve the optimal needle positions that generate the forces in the required directions while keeping a safe distance between the two needles and particles. We applied our method in five typical cases of simultaneous and independent microparticle manipulation, with the closest particle separation of 30 μm.
@inproceedings{isitman2022,title={Simultaneous and Independent Micromanipulation of Two Identical Particles with Robotic Electromagnetic Needles},author={Isitman, Ogulcan and Kandemir, Hakan and Alcan, Gokhan and Cenev, Zoran and Zhou, Quan},booktitle={2022 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)},pages={1--6},year={2022},organization={IEEE},doi={10.1109/MARSS55884.2022.9870468},dimensions={true}}
2021
Non-contact cooperative manipulation of magnetic microparticles using two robotic electromagnetic needles
In this paper, we report a cooperative manipulation method for non-contact robotic electromagnetic needle manipulation system. We employ two 3 degrees of freedom (DOF) robotic electromagnetic needles to achieve an over-actuated manipulator, which can move the particle to any position in the planar workspace from any direction. The redundant DOFs, combined with an optimization-based control approach, enable the manipulator to achieve accurate path following and avoid the collision of needles. Using visual servoing, the developed controller can achieve line following accuracy of 0.33±0.32 μm, square following accuracy of 0.77±0.55 μm, and circle following accuracy of 0.89±0.66 μm with a 4.5 μm diameter superparamagnetic particle. The manipulator can also manipulate a particle along complex paths such as infinity symbol and letter symbols.
@article{isitman21,title={Non-contact cooperative manipulation of magnetic microparticles using two robotic electromagnetic needles},author={I{\c{s}}{\i}tman, O{\u{g}}ulcan and Bettahar, Houari and Zhou, Quan},journal={IEEE Robotics and Automation Letters},volume={7},number={2},pages={1605--1611},year={2021},publisher={IEEE},doi={10.1109/LRA.2021.3137546},url={https://ieeexplore.ieee.org/abstract/document/9661434},dimensions={true},}