基于VINS-Mono的室内机器人定位系统  

Indoor robot positioning system based on VINS-Mono

作　　者：曾超 郑茜颖[1] 程树英[1] ZENG Chao;ZHENG Qianying;CHENG Shuying(College of Physics and Information Engineering,Fuzhou University,Fuzhou 350108,China)

机构地区：[1]福州大学物理与信息工程学院,福建福州350108

出　　处：《传感器与微系统》2022年第11期85-88,共4页Transducer and Microsystem Technologies

基　　金：国家自然科学基金资助项目(61471124);福建省科技厅工业引导性重点项目(2020H0007)。

摘　　要：针对VINS-Mono在室内移动机器人场景中定位精度发散较快的问题,在原系统中融合了轮式里程计的数据,提出了基于VINS-Mono的室内移动机器人定位系统。系统对轮式里程计和陀螺仪数据积分,提供精确运动约束;结合预积分和运动恢复结构(SFM)的运算结果,用松耦合方法计算单目尺度和陀螺仪偏差;用非线性最小二乘优化算法融合预积分数据和相机数据,获得机器人位姿、特征点深度及陀螺仪偏差的最优估计。在公开数据集上进行仿真实验,结果表明:改进后的系统定位精度优于原系统。Aiming at the problem that the positioning precision of VINS-Mono diverges quickly in the indoor mobile robot scene, data of wheel odometer is fused in the original system, and an indoor mobile robot positioning system based on VINS-Mono is proposed.The system integrates the wheel odometer and gyroscope data to provide precise motion constraints;combines the pre-integration and structure from motion(SFM)calculation results to calculate the monocular scale and gyroscope deviation with a loose coupling method.The nonlinear least squares optimization algorithm is used to fuse the pre-integration data and camera data to obtain the optimal estimation of robot pose, feature point depth and gyroscope deviation.The simulation experiment on the public data set shows that the positioning precision of the improved system is better than that of the original system.

关 键 词：运动估计 多传感器融合 同时定位与建图 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TP242[自动化与计算机技术—控制科学与工程]