| 摘要: |
| 为解决卫星失锁条件下车辆的高精度、高可靠性定位问题,结合惯性导航、运动约束、地磁
匹配、激光点云匹配方法的优势,提出了一种基于图优化的惯性/地磁/激光雷达复合定位方案。
首先,采用因子图优化算法,实现惯导预积分信息、运动约束信息、地磁匹配信息、激光雷达点云匹
配信息的异步多源信息融合。然后,在点云匹配失效时,惯性/运动约束/地磁可以实现精度保持,
为点云匹配提供持续可用的先验信息,以避免点云匹配一旦失效后由于先验位姿发散再难匹配的
问题。最后,搭建试验平台完成跑车试验。试验结果表明,该方案可以实现车辆的高精度、高可靠
性定位,点云匹配有效定位精度为1.24m(max),均方根为0.48m,在因点云地图缺失而造成匹配
失效时,惯性/运动约束/地磁可实现定位精度保持在10.29m(max)。 |
| 关键词: 激光雷达点云匹配 惯导 地磁匹配 图优化 |
| DOI： |
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| 基金项目: |
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| Research on Inertial/Geomagnetic/LiDAR Integrated Positioning Technology Based on Graph Optimization |
| ZHAOYu-nan,JIYang,GUOYuan-jiang,LIAng,ZHAO Hao |
| (BeijingInstituteofAutomaticControlEquipment,Beijing100074,China) |
| Abstract: |
| Inordertosolvetheproblemofhigh-precisionpositioningofvehiclesundertheconditionof
satellitelock-out,basedonthecomplementaryadvantagesofinertialnavigation,motionconstraints,geomagneticmatchingandLiDARpointcloudmatchingmethods,
anovelinertial/geomagnetic/LiDARintegratedpositioningschemeusinggraphoptimizationisproposed.
Firstly,thefactorgraphoptimizationalgorithmisusedtorealizetheintegrationofasynchronousmulti-
sourceinformation,includinginertialpreintegrationinformation,
motionconstraintinformation,geomagneticmatchinginformationandLiDAR
pointcloudmatchinginformation.Then,inthecaseofinvalidpointcloudmatching,inertial/motionconstraint/
geomagneticnavigationcanachieveaccuracymaintenance,soastoprovidecontinuouslyavailable
priorinformationforpointcloudmatching,whichcanavoidtherematchproblemforLiDARinthiscase.
Finally,atestplatformisbuilttocompletevehicleroadtests.Theresultsshowthattheproposedscheme
canachievehighprecisionandhighreliabilitynavigation.Thepositioningaccuracyofpointcloudmatching
methodis1.24m(max),theroot-mean-squareis0.48m,andthepositioningaccuracyofinertial/motion
constraint/geomagneticnavigationmethodis10.29m(max)whenthepointcloudmatchingfailsforshort
ofpointcloudmap. |
| Key words: LiDARpointcloudmatching Inertialnavigation Geomagneticmatching Graphoptimization |
