Goals:
The end goal of our project was to have a robotic sawyer arm consistently pocket pool balls. This breaks down into 3 main tasks:
Ball Detection: Use computer vision to detect and identify the scene, including pool balls, the table, and pockets.
Strategy Planning: Create an efficient planning algorithm to determine optimal shot trajectories.
Motion Control: Implement precise control mechanisms for the Sawyer robot to execute shots accurately following the hit plan.
Our group found this project intriguing because it presents a significant challenge in achieving high levels of precision, which is an area where the Sawyer robot has notable limitations. The problem also captivated us due to its emphasis on blending human and robotic interaction in a realistic environment, such as a game of pool. Furthermore, the project offers an exciting opportunity to tackle complex computer vision tasks, which aligns with our interests and adds an additional layer of technical depth. These aspects make the PoolBot project both intellectually stimulating and highly rewarding.
Applications:
Our project could be used as a robotic controller to make pool more accessible. Those who are physically impaired could use our project to participate in pool as it still requires user input to calculate the trajectory of a shot, but takes care of the actual shot movement itself. We also feel Poolbot has the potential in its final form to teach new players how to play pool and what types of angles can they take to achieve the perfect shot.