Review of Continuous-time Trajectory State Estimation Research Based on B-Splines

Multi-source data fusion is a major development trend in state estimation technology in recent years, enhancing the accuracy and robustness of state estimation. However, multi-sensor integration brings new challenges such as timedomain association of high-frequency, different-frequency, and asynchronous data, the accurate calibration of sensor extrinsic parameters, the data distortion correction of continuous acquisition sensors, and fusion of heterogeneous sensor data. Continuous-time trajectory methods naturally have advantages in overcoming these problems. This paper reviews the research on continuous-time trajectory state estimation based on B-splines. Firstly, the theory of continuous-time trajectory state estimation based on B-splines is introduced. Next, different applications to offline calibration and online odometry are systematically classified. Finally, future research directions are discussed.