Monte Carlo Localization Incorporating an Error Correction Vector for Mobile Robots

Yen Cheng Kung, Chen-Chien James Hsu*, Wei-Yen Wang

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

摘要

Nowadays, Monte Carlo Localization (MCL) algorithm is the most commonly used algorithm for a mobile robot to localize itself automatically, and has shown good performances because of its ability to model arbitrary distributions and robustness towards noisy input data. This paper presents an improved Monte Carlo Localization algorithm incorporating an error correction vector, which is calculated from the sensor's error information, and therefore, can achieve better performances in both accuracy and efficiency. Through practical application of the method which incorporates the error correction vector when conducting the program's prediction stage, the particles move closer to the real robot's position. Experimental results show that the proposed algorithm can increase the probability for particles to better estimate the robot's position.

原文英語
主出版物標題New Trends on System Sciences and Engineering - Proceedings of ICSSE 2015
編輯Hamido Fujita, Shun-Feng Su
發行者IOS Press
頁面306-318
頁數13
ISBN(電子)9781614995210
DOIs
出版狀態已發佈 - 2015
事件International Conference on System Science and Engineering, ICSSE 2015 - Morioka, 日本
持續時間: 2015 七月 62015 七月 8

出版系列

名字Frontiers in Artificial Intelligence and Applications
276
ISSN(列印)0922-6389

其他

其他International Conference on System Science and Engineering, ICSSE 2015
國家/地區日本
城市Morioka
期間2015/07/062015/07/08

ASJC Scopus subject areas

  • 人工智慧

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