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基于多传感器融合定位平台，采用误差互补的卡尔曼滤波或误差优化方法是解决室内外无缝定位的主流手段。但是，在缺乏先验地图的城市峡谷和山区等遮蔽、半遮蔽环境，应急救援车载定位系统仍然面临频繁失效问题。基于此，提出了一种基于约束优化的多传感器车载室内外定位方法，设计联合GNSS/IMU/激光雷达的多源融合定位系统，在状态更新模型的基础上，分析了车辆连续起伏过程受力方程约束低成本MEMS高程震荡，设计引入RTK解析状态监测评估约束GNSS可用性，提出联合各传感器误差约束构建集束调整优化方程；分别进行室内、城市和山区场景的实时车载定位测试。实验结果表明，该方法可实现亚米级室内定位和车道级室外定位。
Abstract：With the help of multi-sensor platform, it is the mainstream method to solve indoor and outdoor seamless positioning based on error complementary Kalman filtering or error optimization.However, emergency rescue vehicle positioning systems that lack priori map are faced with frequent failures in sheltered or semi-covered environments such as urban canyons and mountain areas.Based on the above issue, a constraint optimization algorithm for multi-sensor indoor and outdoor vehicle positioning, and a multi-sensor fusion positioning system by GNSS/IMU/Lidar is designed.Based on the state update model, a force equation is analyzed when the vehicle is traveling on an undulating road to constrain low-cost MEMS elevation oscillations, RTK analysis state monitoring and evaluation is introduced to constrain GNSS availability, and a bundle adjustment optimization equation is constructed via the error constraint of each sensor.Finally, real-time vehicle positioning tests in indoor, urban and mountain scenes are conducted, and the experiments show the algorithm can achieve sub-meter indoor positioning and lane-level outdoor positioning.
[1] 杜越.移动机器人智能监控与应急救援关键技术研究[D].成都：电子科技大学，2021.
[2] 张新，徐建华，陈彤，等.面向重大自然灾害的救援装备研究现状及发展趋势[J].科学技术与工程2021,21(25):10552-10565.
[3] CAMPOS C,ELVIRA R,RODRíGUEZ J J G,et al.ORB-SLAM3:An Accurate Open-source Library for Visual,Visual-inertial and Multi-map SLAM[J].IEEE Transactions on Robotics,2020,37(6):1874-1890.
[4] 赵桂玲，姜雨含，李松.IMU标定数学建模及误差分析[J].传感技术学报，2016,29(6):886-891.
[5] SHENG C,FAN G,YU B,et al.Optimized Algorithm for BDS/GPS RTK Suitable for Urban Canyon with Low-cost Receiver[J].Measurement Science and Technology,2020,31(11):115007.1-115007.10.
[6] BIBER P,STRASSER W.The Normal Distributions Transform:A New Approach to Laser Scan Matching[C]∥2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003).Las Vegas:IEEE,2003:2743-2748.
[7] ZHOU B,TANG Z,QIAN K,et al.A LiDAR Odometry for Outdoor Mobile Robots Using NDT Based Scan Matching in GPS-denied environments[C]//2017 IEEE 7th Annual International Conference on CYBER Technology in Automation,Control,and Intelligent Systems (CYBER).Honolulu:IEEE,2017:1230-1235.
[8] KOIDE K,MIURA J,MENEGATTI E.A Portable Three-dimensional LIDAR-based System for Long-term and Wide-area People Behavior Measurement[J].International Journal of Advanced Robotic Systems,2019,16(2):1-16.
[9] SHAN T,ENGLOT B.LeGO-LOAM:Lightweight and Ground-optimized Lidar Odometry and Mapping on Variable Terrain[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).Madrid:IEEE,2019:4758-4765.
[10] QIN C,YE H,PRANATA C E,et al.R-LINS:A Robocentric Lidar-inertial State Estimator for Robust and Efficient Navigation[J/OL].(2019-08-22)[2022-02-16].https://arxiv.org/abs/1907.02233v2.
[11] YE H,CHEN Y,LIU M.Tightly Coupled 3D Lidar Inertial Odometry and Mapping[C]//2019 International Conference on Robotics and Automation (ICRA).Montreal:IEEE,2019:3144-3150.
[12] SHAN T,ENGLOT B,MEYERS D,et al.LIO-SAM:Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems.Las Vegas:IEEE,2020:5135-5142.
[13] ZHANG J,SINGH S.Visual-lidar Odometry and Mapping:Low-drift,Robust,and Fast[C]//2015 IEEE International Conference on Robotics and Automation (ICRA).Seattle:IEEE,2015:2174-2181.
[14] Lidar_align[CP/OL].https://github.com/ethz-asl/lidar_align.
[15] MOORE T,STOUCH D.A Generalized Extended Kalman Filter Implementation for the Robot Operating System[M].Intelligent Autonomous Systems 13.Berlin:Springer Cham,2016.
[16] QUIGLEY M,CONLEY K,GERKEY B,et al.ROS:An Open-source Robot Operating System[J/OL].(2017-10-08)[2022-02-16].http://www.robotics.stanford.edu/～ang/papers/icraoss09-ROS.pdf.
[17] TRIGGS B,MCLAUCHLAN P F,HARTLEY R I,et al.Bundle Adjustment-A Modern Synthesis[C]//International Workshop on Vision Algorithms.Greece:Springer,1999:298-372.
[18] MADSEN K,NIELSEN H B,TINGLEFF O.Methods for Non-linear Least Squares Problems[M].2nd ed.Copenhagen:Technical University of Denmark,2004.
基本信息:
中图分类号:TN96;TP212;U463.67
引用信息:
[1]张子腾,盛传贞,蔚保国,等.基于约束优化的多传感器车载定位方法[J].无线电工程,2022,52(10):1781-1787.
基金信息:
国家重点研发计划(2019YFC1511504)~~
2021-12-02
2021
2022-03-07
2022
1
2022-08-19
2022-08-19
2022-08-19