Month: October 2021

This week, in a team meeting with Tamal and professor Bryon on Monday, professor has pointed out the edge cases that I have missed for the chess game logic. To update the Chess game logic to take account of every possible edge cases that are possible, I researched the chess rules in depth and I made an update on the struct of board state to return the location of each piece name and the piece color to take account of every possible edge cases in the chess game. The board state struct will also contain an int counter to take account of number of turns that have been played, to check the allowed moves for pawn. This will make the check valid process a bit slower, but it is necessary to correctly process many edge cases in the chess game such as  ‘en passant’ state of the pawns and ‘castling’ state (in which two pieces can move in one turn).

I also wrote test benches to check the correctness of my current structure. The current test bench consists of 50 general moves, and each special move per edge case. My logic is currently returning a 100% correctness according to the test bench results.

This week, we continued to work on the three main areas of our project. Creating our custom chessboard, detecting moves with CV, and implementing the chess logic to check for valid moves. We are still working individually but am starting to think about integration on what information needs to be communicated between different modules.

There was one challenge regarding the sample chessboard for CV testing. Working with two chessboards did not work out as well as we expected. The sample chessboard was supposed to be taped together because gluing takes a long time. However, it was difficult to keep the pieces together with tape, and the gaps between pieces made edge detection hard. To mitigate this challenge, we decided to keep the main chessboard in the lab instead of having it in Demi’s apartment for the rest of the semester. Until this week, we mostly worked remotely in our apartments, but from now on we plan to work together in the lab with the main board.

There are no major changes made to our schedule.

This week, I mainly worked on making the case for the chessboard. I chose to use cardboard for the first prototype because cardboard is cheap and easy to cut and drill. I created dxf files using SolidWorks and went to Tech Spark to laser cut them. I also finished gluing the chessboard top, ordered a push button, and connected the LEDs to the RPi and tested controlling the LEDs using the NeoPixel library.

Below is an image of the grids and case glued together with the chessboard on top. The grids are used to separate the light from one LED to other LEDs to ensure that only the correct squares light up. The grids have small holes on the bottom to allow the LED strips to go through. I still have to make the top cover of the electronic case and install the LEDs and push button.

Next week’s goal is to have the full 8×8 LED matrix installed under the board. This will require cutting the LED strip into 64 LEDs and soldering them together. I will test the LEDs lighting up correctly given a coordinate. I will also install the push button once it arrives.

This week I spent time gluing and taping the sample chessboard pieces Demi gave me. This took a significant amount of time because I had to remove the wraps and place the pieces properly so there aren’t gaps between them which would make CV hard.

I also tested my algorithm on images of the actual chessboard that Demi sent me. Attached is an image of the results. The first is the original image, the second is with Canny edge detection. The third one contains blue lines which are the slope 0 or infinity lines in the Hough transform. The yellow color on the squares indicates that these are the squares that have been formed by the line. This works as intended.

Another thing I worked on was ensuring that the pieces are detected properly and the contrast is high enough in our board. This worked fine, but I had to ensure that I use the unblurred image for this because otherwise some of the edges don’t remain sharp anymore. I use the blurred for detecting squares so that the image is less noisy, but the pieces are sometimes considered noise. This result is with the unblurred image. All pieces are detected. The actual edges detected don’t matter in our case, we just want to ensure some edges are detected for each piece.

Because Demi has the board I was unable to test on it with actual pieces, but I have been tested on my imperfect sample board. The sample board is harder to work with because the best pieces were picked for the main board so the ones for the sample board aren’t cut as properly.

I wasn’t able to deliver the test metrics on the actual board because I don’t have it yet. I already talked to Byron and Tamal about this and we decided I would give the chess pieces to Demi and ask her to take pictures because she has the board. On Monday, I will give the pieces to Demi. I am also requesting her to bring the board on Monday so I am able to get some time with it on campus and get the pictures I need.

This week, I plan on forming metrics for the actual chessboard on Monday. I am one day behind schedule, but will be caught up on beginning of next week.

After that, I plan to figure how to get the metrics higher if needed and determine if we need any minimum lighting requirements. I will also look into the metric regarding how “inside” a square a piece needs to be to be detected properly.  This is a problem with the corners of the board because the tall pieces often have edges outside of the square due to the fact that we are looking top-down. I will look into ways to mitigate this.

Lask week, our group spent most  of our time on writing our Design report. We updated our Gantt chart to make updates on changes of current schedule. Anoushka worked on introduction, design requirements, CV trade studies, and CV system description. Demi worked on Architecture, LED trade studies, and hardware system description. Yoorae helped Anoushka on design requirements, and wrote trade studies for AI engine, Project management, and ethical issues sections. We met on Thursday night last weekend to combine our work and finalize our design reports. This week, we discussed ethical issues on Monday to prepare for ethics discussion and ethics assignment for our project. We have concluded that our major goal of the project was to create leisure activity for people who enjoy chess but who are not very familiar with technology by eliminating any software interactions from user’s point of view, but can cause ethical harm by creating more social isolation since our project does not provide any user to user interaction.

One of the most significant risks still remains the accuracy of the CV. This is being managed by ensuring that the board does not have any qualities that would make detection harder. For example, Anoushka found that even slight irregularities on a square can cause issues. We are ensuring that the board does not have any of these. In terms of contingency plans, the main one is to ensure that the user has a way of telling us the detection is wrong. This took some planning to ensure that the game doesn’t become unplayable, but we got help from professors and TA. We decided to light up LEDs to display the detected move and provide the user with a button to press if the detection is wrong. There were no changes to the system diagram after the design report.

Updated Gantt Schedule:

Last week I have spent most of my time on lab hours for writing Design Review Report. The portion I was responsible for was any part that was related to integration of Stockfish Engine of the project. I was also responsible for writing project management portion (including schedule, team member responsibilities, budget, and risk management), related ethical issues, and related work.

I have also finalized the chess logic algorithm that returns boolean values on whether player has made a valid move or not. Since every chess piece has different allowed movements, I have created a class for each chess piece. The main function ‘validate’ will be inputed the current board state, chess piece type,  and a new location that user has indicated. The original state of selected piece (before movement) will be reachable in a board class that is passed into the function. If the movement is validated from the piece class as a possible movement, the function will return a tuple of new coordinates for the piece, else, it will return Null and the function will return false.

I am also working on a transition function for Chess AI integration. Anoushka has updated coordinate algorithm from CV edge detection, which has to be translated to be computed with bit boards in Stockfish engine.

From next week, I will be working with Anoushka with the  background subtraction algorithm to help her with updating board states.

This week I spent most of my time practicing for Design Review presentation. I practiced speaking with my teammates and practiced answering possible questions that can be asked to me. I also started writing Design Review Report, and wrote a code in C that can detect any illegal moves in Chess.