高技术通讯2024，Vol.34Issue(4)：413-419,7.DOI:10.3772/j.issn.1002-0470.2024.04.009
基于因子图的多传感器融合定位方法
Multi-sensor fusion localization method based on factor graph
摘要
Abstract
Aiming at the problems of low localization accuracy and insufficient robustness of mobile robots using single sensor or loosely coupled localization in indoor environment,a multi-sensor tightly coupled localization algorithm based on factor graph is proposed.The algorithm receives data from inertial measurement unit(IMU),wheel en-coder and 2D lidar,and constructs IMU pre-integration factor,wheel odometry factor,pose prior factor and laser odometry factor.The state information of the mobile robot is obtained after incremental optimization of these factors through the factor graph,and the drift of the IMU is estimated and corrected in real time.Experimental results show that the localization algorithm can effectively improve the localization accuracy and robustness of mobile robots in unknown or known environments.关键词
移动机器人/因子图优化/紧耦合/惯性测量单元(IMU)预积分Key words
mobile robot/factor graph optimization/tightly-coupled/inertial measurement unit (IMU) pre-integration引用本文复制引用
孙晨阳,张群莉,潘聪,邵兵兵,方灶军..基于因子图的多传感器融合定位方法[J].高技术通讯,2024,34(4):413-419,7.基金项目
国家自然科学基金(U1909215,92048201,52127803),浙江省重点研发计划(2022C01096),浙江省自然科学基金(LD22E050007),中科院装备研制项目(YJKYYQ20200030)和宁波市2025重大专项(2021Z020)资助项目. （U1909215,92048201,52127803）
