This week, our group focused on refining our approach to the computer vision and physics simulation components of the project. After meeting with our professor and TA, we reassessed our hardware requirements and decided that using a single-board computer, such as the Jetson Orin Nano or Raspberry Pi, is unnecessary. Instead, we will run all computer vision and physics simulation tasks on our personal computers, allowing us to prioritize algorithm development while addressing hardware needs as they arise.
Luke spent much of the week assisting with research on both the computer vision and physics simulation aspects of the project. He also worked on the Design Review presentation and Written Design Review, including drafting sketches for the mount that will hold the overhead camera above the pool table. Next week, he will begin constructing the mount and ordering the necessary parts, as the pool table is set to be delivered soon.
Kevin focused on implementing computer vision for boundary edges and pocket detection. He developed edge detection algorithms to determine the table’s physical dimensions and started working on thresholding techniques to identify pocket positions. Additionally, he researched ball detection and categorization methods for later stages of the CV pipeline, compiling useful resources for future implementation.
Samuel concentrated on the physics simulation, researching existing codebases, papers, and videos that could inform our approach. He also conducted initial benchmark testing by playing three games of 9-ball with Luke to establish a baseline for shot efficiency. Furthermore, he updated our block diagram and Gantt chart to reflect the removal of the Nvidia Jetson, as we will now directly connect the camera/LiDAR to a computer.
Overall, our team remains on schedule, and we will continue refining our design while moving into the implementation phase. Next week, we plan to begin assembling the system, conduct additional benchmark testing with the newly ordered pool table, and further develop our physics simulation and computer vision algorithms.