Online Calibration

Online calibration addresses the challenge of maintaining accurate and reliable model predictions in dynamic environments where sensor characteristics or system parameters may change over time. Current research focuses on developing online calibration methods for diverse applications, employing techniques such as adaptive risk control, transformer networks, and tightly-coupled sensor fusion with optimization-based approaches. These advancements improve the accuracy and robustness of various systems, ranging from autonomous navigation and robotics to nuclear reactor monitoring and financial modeling, by enabling continuous adaptation to changing conditions. The resulting improvements in prediction accuracy and reliability have significant implications for safety, efficiency, and decision-making across numerous fields.