ARAtronics Research Center (Applied-Science & Robotics Laboratory for Applied-Mechatronics) is a multi-disciplinary research and development center for the opto-mechatronics solutions. The typical Mechatronics systems are keen to implement a typical closed-loop feedback control for any automation systems. In the ARAtronics Research Center, we are developing extremely sensitive micro sensors and actuators could enrich the typical Mechatronics close-loop feedback algorithms in a very significant way. The importance of using these micro-optical sensors and integrated with the typical Mechatronics systems will open the door to introduce a new technology based on the opto-mechatronics devices. One of our goals is to integrate some of the optical components to the typical micro-electro-mechanical systems (MEMS) to build a new device that will be very fast enough to deal with the control feedback and automation signals because it depends on speed of light. We are focusing into the process of fabrication, and signal processing for these new smart sensors and actuators. Also, the integration with several applications in Mechatronics and robotics that used at any automated process will be part of our research not only from the analytical studies but also from the experimental and implementation point of views.Â
A. R. Ali and M. Y. Selim, "Design and Integration of a Multi-Axial Tactile Sensor for Dexterous Manipulation by Humanoid Robots for Industrial Applications," Results in Engineering, vol. –, Art. no. 108494, 2025.Â
A. R. Ali and F. Ezzeldin, "A Bond Graph Model for VOC Detection via Polymeric Whispering-Gallery-Mode Optical Sensors," in Proc. 2025 7th Novel Intelligent and Leading Emerging Sciences Conference (NILES), pp. 435–438, 2025.Â
A. R. Ali and A. M. Tarek, "Model-Free MRAC Using Sensor-Based Reference Estimation and Real-Time Lyapunov Control," in Proc. 2025 International Telecommunications Conference (ITC-Egypt), pp. 453–458, 2025.Â
A. R. Ali and H. Kamal, "Hybrid RF-MLP Model for Enhanced Fault Detection in Power Transmission Systems Using Data Resampling Techniques," in Proc. 2025 International Telecommunications Conference (ITC-Egypt), pp. 364–369, 2025.Â
A. R. Ali, M. W. A. Ramadan, and M. Helal, "Real-Time Detection of Surface Cracks in Wood Using Deep Learning-Based Image Analysis for Quality Control," in Proc. 2025 International Telecommunications Conference (ITC-Egypt), pp. 740–745, 2025.Â
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