Vehicle High-precision Positioning Technique Based on Multi-sensors Information Fusion

doi:10.3969/j.issn.1004-132X.2022.19.013

Abstract

Abstract: In order to solve the positioning error problems of multi-axle emergency rescue vehicles driving in complex environments， a combined positioning system was designed based on multi-information fusion. The positioning system was mainly composed of a front-end odometer and a back-end optimization model. The three-axis vehicle kinematics modeling was completed， the inertial measurement unit-based kinematics prediction equation and global positional system-based kinematics observation equation were derived， the state was updated through the Kalman filter， and the construction of the front-end odometer was completed. The external reference calibration tool was designed based on iterative closest point matching algorithm， and a feature point cloud matching model was constructed to complete the back-end model optimization. Finally， after simulation and experiments were carried out， the results show that the positioning errors of the system are less than 3.45 cm， the angle errors are less than 0.10 degrees， the accuracy and stability are greatly improved.

Key words: combined positioning system, front-end odometer, point cloud matching, information fusion

摘要： 为解决多轴应急救援车辆在复杂环境行驶时的定位误差问题，设计了一种基于多信息融合的组合定位系统，该定位系统主要由前端里程计和后端优化模型组成。首先完成三轴车运动学建模，推导出基于惯性测量单元的运动学预测方程和基于全球定位系统的运动学观测方程，通过Kalman滤波器进行状态更新，完成前端里程计的构建；然后设计了基于迭代最近点匹配算法的外参标定工具，并构建了特征点云匹配模型，完成后端模型优化；最后进行了仿真与实验，研究结果表明，该系统定位误差为±3.45 cm，角度误差为±0.10°，准确性、稳定性均得到了很大的提高。

关键词: 组合定位系统, 前端里程计, 点云匹配, 信息融合

CLC Number:

U495

SHI Xiaobo, ZHAO Dingxuan, KONG Zhifei, NI Tao, ZHAO Xiaolong, GUO Qinghe. Vehicle High-precision Positioning Technique Based on Multi-sensors Information Fusion[J]. China Mechanical Engineering, 2022, 33(19): 2381-2387.

师小波, 赵丁选, 孔志飞, 倪涛, 赵小龙, 郭庆贺. 基于多传感器信息融合的车辆高精度定位技术[J]. 中国机械工程, 2022, 33(19): 2381-2387.

References

［1］MICHAEL L， KOOKTAE L. Outdoor Target Positioning Using Wii Remote IR Camera and Signal Modulation［J］. Sensors， 2020， 20（8）：2163-2174.
［2］韩明瑞，周波，钱堃，等. 基于激光雷达的室外移动机器人三维定位和建图［J］. 华中科技大学学报（自然科学版）， 2015， 43（S1）：315-318.
HAN Mingrui， ZHOU Bo， QIAN Kun， et al. Three-dimensional Positioning and Mapping of Outdoor Mobile Robots Based on Lidar［J］. Journal of Huazhong University of Science and Technology（Natural Science Edition）， 2015， 43（S1）：315-318.
［3］胡胜豪. 室外移动机器人的定位与运动控制研究［D］. 哈尔滨：哈尔滨工业大学， 2016.
HU Shenghao. Research on Positioning and Motion Control of Outdoor Mobile Robot［D］. Harbin：Harbin Institute of Technology， 2016.
［4］汪涛. 智能行驶车辆定位技术研究［D］. 长春：吉林大学， 2017.
WANG Tao. Research on Intelligent Driving Vehicle Positioning Technology［D］. Changchun：Jilin University， 2017.
［5］LI Dengao， WEI Zheng， ZHAO Jumin， et al. Integrated Positioning Algorithm Based on GPS/WLAN［J］. Concurrency and Computation：Practice and Experience， 2019， 31（17）：30-46.
［6］JI Z， SANJIV S. Laser-Visual-Inertial Odometry and Mapping with High Robustness and Low Drift［J］. Journal of Field Robotics， 2018， 35（8）：1242-1264.
［7］HE Zhimin， PENG Lin， HAN Haiyun， et al. Research on Indoor and Outdoor Comprehensive Positioning Technology Based on Multi-source Information Assistance［J］. Procedia Computer Science， 2020， 166（9）：361-365.
［8］李旭，张为公. 基于联邦滤波的智能车辆多传感器组合导航的研究［J］. 中国机械工程， 2008， 19（12）：1446-1451.
LI Xu， ZHANG Weigong. Research on Intelligent Vehicle Multi-sensor Integrated Navigation Based on Federal Filtering［J］. China Mechanical Engineering， 2008， 19（12）：1446-1451.
［9］付廷强. 基于GNSS/IMU/视觉多传感融合的组合导航定位算法研究［D］. 上海：上海交通大学， 2019.
FU Tingqiang. Research on Integrated Navigation and Positioning Algorithm Based on GNSS/IMU/ Visual Multi-sensor Fusion［D］. Shanghai：Shanghai Jiaotong University， 2019.
［10］祝会忠，路阳阳，徐爱功，等. 长距离GPS/北斗卫星导航定位系统网络RTK方法［J］. 武汉大学学报（信息科学版）， 2020， 7（02）：1-9.
ZHU Huizhong， LU Yangyang， XU Aigong， et al. Long-range GPS/Beidou Satellite Navigation and Positioning System Network RTK Method［J］. Journal of Wuhan University（Information Science Edition）， 2020， 7（2）：1-9.
［11］ZHANG J， SINGH S. Low-drift and Real-time Lidar Odometry and Mapping［J］. Autonomous Robots， 2017， 41（3）：401-416.
［12］马芳武，史津竹，葛林鹤，等. 无人驾驶车辆单目视觉里程计的研究进展［J］. 吉林大学学报（工学版）， 2020， 50（3）：765-775.
MA Fangwu， SHI Jinzhu， GE Linhe， et al. Research Progress of Monocular Visual Odometer for Driverless Vehicles［J］. Journal of Jilin University（Engineering Science Edition）， 2020， 50（3）：765 -775.
［13］HAO Yushi， XU Aigong， WANG Xin， et al. A Modified Extended Kalman Filter for a Two-antenna GPS/INS Vehicular Navigation System［J］. Sensors， 2018， 18（11）：3809-3820.
［14］KIM D C， MIN K， KIM H， et al. Vehicle Sideslip Angle Estimation Using Deep Ensemble-based Adaptive Kalman Filter［J］. Mechanical Systems and Signal Processing， 2020， 144：106862.
［15］孙涛，徐正进，尤霖，等. 基于卡尔曼滤波器的智能车过弯时间优化控制算法［J］. 中国机械工程， 2015， 26（19）：2693-2697.
SUN Tao， XU Zhengjin， YOU Lin， et al. Intelligent Vehicle Cornering Time Optimization Control Algorithm Based on Kalman Filter［J］. China Mechanical Engineering， 2015， 26（19）：2693-2697.
［16］楼晓春. 基于扩展Kalman滤波器算法的移动机器人同步定位与建图［J］. 中国机械工程， 2011， 22（24）：2927-2930.
LOU Xiaochun. Synchronous Positioning and Mapping of Mobile Robots Based on Extended Kalman Filter Algorithm［J］. China Mechanical Engineering， 2011， 22（24）：2927-2930.
［17］张建华，张洪华，刘璇. 基于PageRank的SLAM后端优化研究［J］. 华中科技大学学报（自然科学版）， 2019， 47（4）：61-66.
ZHANG Jianhua， ZHANG Honghua， LIU Xuan. Research on SLAM Backend Optimization Based on PageRank［J］. Journal of Huazhong University of Science and Technology（Natural Science Edition）， 2019， 47（4）：61-66.
［18］CARLOS S B. CERIANI S， TADDEI P， et al. Global Matching of Point Clouds for Scan Registration and Loop Detection［J］. Robotics and Autonomous Systems， 2020， 123.
［19］葛平淑，王荣本，郭烈. 基于模糊逻辑的六轮月球车路径跟踪控制［J］. 吉林大学学报（工学版）， 2011， 41（2）：503-508.
GE Pingshu， WANG Rongben， GUO Lie. Path Tracking Control of Six-wheel Lunar Rover Based on Fuzzy Logic［J］. Journal of Jilin University（Engineering Science Edition）， 2011， 41（2）：503-508.
［20］YANG J L， LI H D， CAMPBELL D， et al. Go-ICP：a Globally Optimal Solution to 3D ICP Point-Set Registration. ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence， 2016， 38（11）：2241-2254.
［21］姜晓通，戴宁，张长东，等. 基于“滑移”主方向自适应采样的ICP 算法优化研究［J］. 中国机械工程， 2014， 25（4）：497-502.
JIANG Xiaotong， DAI Ning， ZHANG Changdong， et al. Research on ICP Algorithm Optimization Based on “Slap” Principal Direction Adaptive Sampling［J］. China Mechanical Engineering， 2014， 25（4）：497-502.

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[2]	HU Yanping, LIU Fei, WEI Zhenya, ZHAO Linfeng. Vehicle Tracking of Information Fusion for Millimeter-wave Radar and Vision Sensor [J]. China Mechanical Engineering, 2021, 32(18): 2181-2188.
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[5]	ZHANG Weiwei1;MI Zeyang1;XIAO Lingyun2;QIAN Yubin1. Driver Yawning Detection Based on Deep Convolutional Network and Tracking with Online Learning [J]. China Mechanical Engineering, 2019, 30(08): 902-911.
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[7]	Zhang Qiang, Wang Haijian, Li Liying , Wen Xuezhen , Nguyen Viet Tuyen, . Failure Diagnosis of Shearer Picks Based on Information Fusion from Multi Sensors [J]. China Mechanical Engineering, 2016, 27(17): 2334-2340.
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[9]	Zhang Qiang, Wang Haijian, Jing Wang, Mao Jun, Yuan Zhi, Hu Denggao. Shearer's Coal-rock Recognition System Based on Fuzzy Neural Network Information Fusion [J]. China Mechanical Engineering, 2016, 27(02): 201-208.
[10]	JIANG Mo-Lu, LIU Sai-Yuan. Fault Diagnosis Approach Study of Bayesian Networks Based on Multi-characteristic Information Fusion [J]. China Mechanical Engineering, 2010, 21(8): 940-945,967.
[11]	LIU Jian, TUN Xiong-Chi, JI Shi-Ming. Study on Oil Quality Evaluation Method and Its Implementation Based on Multi-information Fusion [J]. China Mechanical Engineering, 2010, 21(21): 2614-2618.
[12]	Wang Tanbin;Chen Wuwei;Jiao Jun;Wang Minglei. Study on Navigation of Intelligent Vehicles Based on Multi-sensor Fusion [J]. J4, 2009, 20(11): 0-1385.
[13]	Yue Jianfeng;Zhang Cuixuan;Li Liangyu . MIG Welding Robot Welding Quality Control Based on Multi-information Fusion [J]. J4, 2009, 20(09): 0-1016.
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[15]	Rao Hong;Fu Mingfu;Xie Mingxiang;Yang Guotai. Research on the Equipment Fault Diagnosis on the Basis of Decision Level Information Fusion [J]. J4, 2009, 20(04): 0-388.