当前位置: X-MOL 学术Front. Inform. Technol. Electron. Eng. › 论文详情
Novel 3D point set registration method based on regionalized Gaussian process map reconstruction
Frontiers of Information Technology & Electronic Engineering ( IF 1.033 ) Pub Date : 2020-05-21 , DOI: 10.1631/fitee.1900457
Bo Li, Yu Zhang, Wen-jie Zhao, Ping Li

Point set registration has been a topic of significant research interest in the field of mobile intelligent unmanned systems. In this paper, we present a novel approach for a three-dimensional scan-to-map point set registration. Using Gaussian process (GP) regression, we propose a new type of map representation, based on a regionalized GP map reconstruction algorithm. We combine the predictions and the test locations derived from the GP as the predictive points. In our approach, the correspondence relationships between predictive point pairs are set up naturally, and a rigid transformation is calculated iteratively. The proposed method is implemented and tested on three standard point set datasets. Experimental results show that our method achieves stable performance with regard to accuracy and efficiency, on a par with two standard methods, the iterative closest point algorithm and the normal distribution transform. Our mapping method also provides a compact point-cloud-like map and exhibits low memory consumption.
更新日期:2020-05-21

 

全部期刊列表>>
智控未来
聚焦商业经济政治法律
跟Nature、Science文章学绘图
控制与机器人
招募海内外科研人才,上自然官网
隐藏1h前已浏览文章
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
x-mol收录
湖南大学化学化工学院刘松
上海有机所
李旸
南方科技大学
西湖大学
伊利诺伊大学香槟分校
支志明
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug