Trajectory Estimation

Trajectory estimation focuses on accurately determining the path of an object or system over time, a crucial task across diverse fields. Current research emphasizes robust methods for handling noisy or incomplete data, employing techniques like Kalman filtering, Gaussian processes, spline-based approaches, and factor graph optimization, often incorporating data from multiple sensor modalities (e.g., LiDAR, IMU, GNSS, cameras). These advancements are driving improvements in applications ranging from autonomous robot navigation and retail analytics to sports performance analysis and spacecraft control, enabling more precise localization and improved decision-making. The development of novel metrics and initialization strategies further enhances the accuracy and reliability of trajectory estimation algorithms.