Physical Parameter

Estimating physical parameters from various data sources, such as audio, video, and LiDAR signals, is a burgeoning research area aiming to characterize the properties of objects and environments. Current research focuses on developing robust and accurate estimation methods, employing techniques like neural networks (including Physics-Informed Neural Networks and neural ordinary differential equations), and normalizing flows, often coupled with physics engines or incorporating physical constraints to improve accuracy and generalization. These advancements have significant implications for diverse fields, including robotics, environmental monitoring, and industrial process optimization, by enabling more precise modeling and control of complex systems.