Ball Rolling

Research on ball rolling encompasses diverse applications, from robotic manipulation and sports analytics to medical imaging and theoretical computer science. Current investigations focus on developing accurate and efficient models for predicting ball trajectories, often employing machine learning techniques like differentiable factor graphs and neural networks, alongside advanced algorithms for image reconstruction and data preprocessing to mitigate bias. These advancements are improving the accuracy of simulations, enabling better robotic control, and facilitating more sophisticated analyses in various fields, including sports performance and medical diagnostics. The development of robust and efficient algorithms for handling complex ball dynamics and contact simulations remains a key area of ongoing research.