Registration of TLS and MLS Point Cloud Combining Genetic Algorithm with ICP

被引：0
|
作者：
Yan L. [1 ]
Tan J. [1 ]
Liu H. [1 ]
Chen C. [1 ]
机构：
[1] School of Geodesy and Geomatics, Wuhan University, Wuhan
来源：
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | 2018年 / 47卷 / 04期
关键词：
Genetic algorithm; ICP; Mobile laser scanning; Point cloud registration; Terrestrial laser scanning;
D O I：
10.11947/j.AGCS.2018.20170235
中图分类号：
学科分类号：
摘要：
Large scene point cloud can be quickly acquired by mobile laser scanning (MLS) technology, which needs to be supplemented by terrestrial laser scanning (TLS) point cloud because of limited field of view and occlusion.MLS and TLS point cloud are located in geodetic coordinate system and local coordinate system respectively.This paper proposes an automatic registration method combined genetic algorithm (GA) and iterative closed point ICP to achieve a uniform coordinate reference frame.The local optimizer is utilized in ICP.The efficiency of ICP is higher than that of GA registration, but it depends on a initial solution.GA is a global optimizer, but it's inefficient.The combining strategy is that ICP is enabled to complete the registration when the GA tends to local search.The rough position measured by a built-in GPS of a terrestrial laser scanner is used in the GA registration to limit its optimizing search space.To improve the GA registration accuracy, a maximum registration model called normalized sum of matching scores (NSMS) is presented.The results for measured data show that the NSMS model is effective, the root mean square error (RMSE) of GA registration is 1~5 cm and the registration efficiency can be improved by about 50% combining GA with ICP. © 2018, Surveying and Mapping Press. All right reserved.
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页码：528 / 536
页数：8
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