Mechanical Automation with Vision: A Design for Rubik's Cube Solver
This work addresses the challenge of building a low-cost, automated Rubik's Cube solver for hobbyists and educational purposes, but it is incremental as it combines existing methods like YOLO and Kociemba's algorithm with custom hardware.
The paper tackles the problem of automating Rubik's Cube solving by integrating mechanical manipulation with computer vision, achieving an average solving time of approximately 2.2 minutes using YOLOv8 for detection and the Kociemba algorithm for solution generation.
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.