For this week, I continued focusing on preparing the software side of the project for digital board-state tracking and the chess logic since we have not yet gotten a camera for our setup. Since I couldn’t work on the camera capture and calibration pipeline, I researched how the computer vision output will eventually feed into the digital chessboard representation, move validation, and move logging. One key component to this was looking into the python library, python-chess, which would serve as the foundation for legal moves, updating board after valid move, and generating a PGN move history.
I also began to look into how the flow of moves should be represented internally, which includes the starting square, ending square, move number, and timestamp, so that the move detection and logging can be handled more consistently later on. I did some basic research on how to have the software components run on the NVIDIA Jetson Orin Nano and how the modules should be separated so that the board state logic can potentially be tested before the vision hardware integration.
As of now, my progress has been slightly shifted since we don’t have the camera for the configuration quite yet, but I am using that time to work more on the software components. Next week, I plan to continue developing the digital board-state representation and begin testing move detection and validation using either manually generated or simulated board states. This will help me to check move validation thru the library python-chess. Another thing that I hope to accomplish is an initial move logging structure so that valid moves can be stored in sequence.
Prototyping of board-state tracking + move logging:
