State estimation of multi-sensor systems based on error-state Kalman.

ABSTRACT: With the rapid advancement of multi-sensor systems, the capabilities of robots in complex scenes are gradually improving. A multi-sensor system state estimation algorithm based on error-state Kalman filter is proposed to address the issues of noise interference, sensor data loss, and interference from moving targets in dynamic scenes. Firstly, the state estimation method of multi-sensor system based on sequential fusion framework is designed to effectively integrate and process different sensor data. On this basis, further research is conducted to design a lightweight detection algorithm based on multi-sensor data for identifying and processing moving targets in dynamic scenes, thereby reducing their interference with state estimation. Finally, a sequential fusion odometer based on error-s

SUBMITTER: Liu Y 

PROVIDER: S-EPMC12742780 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature