LINS-GNSS:滤波与优化耦合的GNSS/INS/LiDAR巡检机器人定位方法  

LINS-GNSS:filter and optimization coupled GNSS/INS/LiDAR positioning method for inspection robot localization

作　　者：文刚 周仿荣 李涛[2] 马御棠 裴凌[2] 刘亚东[3] 钱国超 潘浩 WEN Gang;ZHOU Fangrong;LI Tao;MA Yutang;PEI Ling;LIU Yadong;QIAN Guochao;PAN Hao(Electric Power Research Institute/Joint Laboratory of Power Remote Sensing Technology,Yunnan Power Grid Co.,Ltd.,Kunming 650217;Shanghai Key Laboratory of Navigation and Location-Based Services,Shanghai Jiao Tong University,Shanghai 200240;School of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240)

机构地区：[1]云南电网有限责任公司电力科学研究院/电力遥感技术联合实验室,昆明650217 [2]上海交通大学上海市北斗导航与位置服务重点实验室,上海200240 [3]上海交通大学电子信息与电气工程学院,上海200240

出　　处：《南京信息工程大学学报（自然科学版）》2023年第1期85-93,共9页Journal of Nanjing University of Information Science & Technology（Natural Science Edition）

基　　金：南方电网有限责任公司科技项目(YNKJXM20191246);国家自然科学基金(61873163);上海市科技创新行动计划项目(20511103103)。

摘　　要：为了能够更加灵活地执行变电站巡检任务,非固定线路的机器人巡检技术越来越受到关注.如何在复杂的变电站环境中实现高精度的定位是机器人在变电站执行巡检任务时需要解决的核心问题.单一传感器难以满足变电站可靠定位的要求,因此,本文设计了多传感器融合的LINS-GNSS定位方法.其前端基于迭代误差状态卡尔曼滤波框架将激光雷达和惯性导航进行紧耦合,在每次迭代中生成新的特征对应关系递归地校正估计状态.后端使用因子图优化的方法将卫星导航的定位结果与LINS后端输出的定位结果松耦合.优化过程中先将局部坐标系与全局坐标系对齐,再将卫星导航的位置约束作为先验边添加到后端的因子图中,最后将定位结果在全局坐标系下输出.为了评估LINS-GNSS系统在变电站环境中的性能,本文在实际变电站中进行了测试.实验结果表明,LINS-GNSS系统在变电站环境中可以达到优于0.5 m的定位精度,且比现有最佳算法LIO-SAM定位精度更高.In the past few years,robots have become an important means of substation inspection,and robotic inspection technology for non-fixed lines has received increasing attention in order to perform inspection tasks more flexibly.How to achieve high-precision positioning in complex substation environment is one of the core problems to be solved.It is difficult for a single sensor to meet the requirements of reliable positioning in substations,therefore,this paper designs a multi-sensor fusion LINS-GNSS positioning method.Its front-end tightly couples LiDAR and inertial navigation based on an iterative error-state Kalman filter framework,which recursively corrects the estimated state by generating new feature correspondences in each iteration.The back-end uses a factor graph optimization approach to loosely couple the localization results from the satellite navigation with the localization results output from the LINS back-end.The optimization process first aligns the local coordinate system with the global coordinate system,then adds the position constraints of the GNSS as a priori edge to the factor graph in the back-end,and finally outputs the positioning results in the global coordinate system.In order to evaluate the performance of the LINS-GNSS system in the substation environment,this paper conducted field tests under real scenarios.The experimental results show that the LINS-GNSS system can achieve a positioning accuracy better than 0.5 m in the substation environment,better than LIO-SAM.

关 键 词：多传感器融合 因子图优化 卡尔曼滤波 卫星导航 激光SLAM 

分 类 号：V249.3[航空宇航科学与技术—飞行器设计]