This week I accomplished establishing a pipeline to interpreting the camera data and calculating the coordinates of where the gantry system needs to move. After some discussion and research, I also changed the decision to use the OAK-D Pro depth camera rather than the D435. I initially started by helping Josiah with running experiments to test whether a simple kinematic model would suffice to accurately estimate the landing trajectory. However, we figured that too small deviances in the measurement would result in very large estimation errors, so I had to do more research on other more complex models. My work this week for the camera system pipeline mainly revolved around literature review for the Kalman Filter to predict the trajectory of the ball based on it’s past movements. I also looked at hough circle or YOLO models as feature extraction based vs CNN based approaches to implementing ball tracking.Â
I mainly accomplished what I set out to do last week, although I would like to get some preliminary implementation done with the CV system, even if it’s on a rudimentary camera with no depth information. I will also need to consult with more experienced sources in this field to finalize and recognize the trade offs between each of my implementations, perhaps faculty in field of robotics or computer vision. Next week I will mainly aim to work on a first implementation of the ball tracking mechanism whilst I wait for the camera to arrive, as I do not need any depth information for that to be functional.