Map building of unknown environment using PSO-tuned enhanced Iterative Closest Point algorithm

Chen-Chien James Hsu, Hua En Chang, Yin Yu Lu

研究成果: 書貢獻/報告類型會議論文篇章

6 引文 斯高帕斯(Scopus)

摘要

Iterative Closest Point (ICP) algorithm is widely used in 2D and 3D spatial and geometric alignment. There are many variants of the ICP algorithm, proposing methods to minimize the sum of Euclidean distances between two clouds of scanning points for map building of an unknown environment by a mobile robot. Considering simplicity and computational efficiency, this paper proposes an enhanced-ICP incorporating a Particle Swarm Optimization (PSO) to effectively filter out outliers and avoid the false matching points during the map building process. Experimental results showed that, the proposed PSO-tuned enhanced-ICP can effectively reduce the accumulated errors to improve the map building accuracy by circumventing the problems of local optimal solutions resulted from the outliers and false matching points during the map building process.

原文英語
主出版物標題ICSSE 2013 - IEEE International Conference on System Science and Engineering, Proceedings
頁面279-284
頁數6
DOIs
出版狀態已發佈 - 2013 十一月 18
事件IEEE International Conference on System Science and Engineering, ICSSE 2013 - Budapest, 匈牙利
持續時間: 2013 七月 42013 七月 6

出版系列

名字ICSSE 2013 - IEEE International Conference on System Science and Engineering, Proceedings

其他

其他IEEE International Conference on System Science and Engineering, ICSSE 2013
國家/地區匈牙利
城市Budapest
期間2013/07/042013/07/06

ASJC Scopus subject areas

  • 控制與系統工程

指紋

深入研究「Map building of unknown environment using PSO-tuned enhanced Iterative Closest Point algorithm」主題。共同形成了獨特的指紋。

引用此