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

被引：0

作者：

Lü, Jiajun ^{[1
]}

Lang, Xiaolei ^{[1
]}

Li, Baorun ^{[1
]}

Liu, Yong ^{[1
]}

机构：

[1] College of Control Science and Engineering, Zhejiang University, Hangzhou

来源：

Jiqiren/Robot | 2024年 / 46卷 / 06期

关键词：

B-spline; continuous-time trajectory; mapping); sensor calibration; SLAM (simultaneous localization; state estimation;

D O I：

10.13973/j.cnki.robot.230302

中图分类号：

学科分类号：

摘要：

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 time-domain 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. © 2024 Chinese Academy of Sciences. All rights reserved.

引用

页码：743 / 752

页数：9

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