Research Publications

The core mechanical system is built around three stepper motors for physical manipulation, a microcontroller for hardware control, a camera and YOLO detection model for real-time cube state detection. A significant software component is the development of a user-friendly graphical user interface (GUI) designed in Unity. The initial state after detection from real-time YOLOv8 model (Precision 0.98443, Recall 0.98419, Box Loss 0.42051, Class Loss 0.2611) is virtualized on GUI. To get the solution, the system employs the Kociemba's algorithm while physical manipulation with a single degree of freedom is done by combination of stepper motors' interaction with the cube achieving the average solving time of ~2.2 minutes.

This research was led by Nishan Khanal. The R&D Unit initiated the work of research in our community. The first notable work of this unit includes a collaboration with Racheal Lau regarding a talk on research. Under the supervision of Asst. Professor Er. Dinesh Banyia Khastri, R&D Unit applied for the research grant proposed by NCE College. For this research, the R&D Unit of ECAST collaborated with the Central Department of Physics, TU for resources. This research aims to develop a new algorithm in the field of image processing using a diffusion model. The research on completion will develop an algorithm for undoing and redoing edited images.