This week we focused on finishing our remaining tasks and our final testing/integration testing. We added a physical button instead of the purely software key. We finished adding a UI for parcheesi and the appropriate on board implementation. We improving our move planning algo and detection for the board. Cleaned up board swapping between chess/checkers and parcheesi for our demo.
Until the demo we still need to fine tune a few things mainly visual in terms of the board.
Tests:
Motors:
Move Completion time: 4.42
Placement accuracy across all 3 games: (100%)
Note/Change: This number was initially more inaccurate but after tuning down the speed and slowing down the magnet pick up and let go we were able to increase our accuracy.
Magnet Pickup: 100% succesful
CV System (Pi + Camera):
Diff Accuracy alone: 82% (detection of extra or too few squares means a wrong detection)
Full CV Accuracy with game rules and board state: 100%
ML Accuracy: 62% (initially)
Promotion Accuracy and Detection: 100%
Change: Our low ML Accuracy caused us to switch from a trained model to a system that stored pieces on the side of the chessboard and remembered them. This meant that for promotions it could take from the used pieces. Could also detect when player 1 promotes to one of these pieces and takes it.
Auto detection of Outer board: 75%
Auto detection of Inner Board if Outer board correct: 70%
Change: Made the user manually pick the corner points in software. Coupled with changing the outer board corners to a unique color for auto detection and then using fixed geometry for inner board and then manual user confirmation.
Player 2 GUI:
Ran tests for invalid move detection on all 3 games: 100%
Ran tests for correctly updating given the move from the Pi:
For Chess: 100%
For Checkers: 100%
For Parcheesi: 100%
Integration Tests:
Ran through 10 full games of Chess, Checkers, and Parcheesi.
Ensured no build up in error, ensured software state matched physical state, ensured accuracy throughout the game: 100%
Session reliability: 5 game of each type was played back to back to back to ensure we didn’t need to recalibrate (for at least an hour). Total duration took 4 hours.
User Enjoyment: Ran study to ensure > 80% like it more than strictly virtual We received 100% enjoyment. (Tested on 10 people)