HybridSLAM: A Robust Algorithm for Simultaneous Localization and Mapping

被引：0
|
作者：
Monjazeb, Amir [1 ]
Sasiadek, Jurek Z. [1 ]
Necsulescu, Dan [2 ]
机构：
[1] Carleton Univ, Dept Mech & Aerosp Engn, 1125 Colonel Dr, Ottawa, ON, Canada
[2] Univ Ottawa, Dept Mech Engn, Ottawa, ON, Canada
来源：
ICIMCO 2015 PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL. 2 | 2015年
关键词：
Simultaneous Localization and Mapping (SLAM) Problem; Unscented HybridSLAM; Unscented Kalman Filter; Position Error; Time and Measurement Update;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper addresses an ongoing research on a novel approach to Simultaneous Localization and Mapping problem called Unscented HybridSLAM. The main contribution of this paper is to develop the map update formulas along with proof results in order to investigate the validation of the map evolution. The investigation is presented using the help of simulations in terms of robustness, map fusion, and the update process. Results clearly show that as the vehicle travels along the path and the map evolves, the Unscented HybridSLAM algorithm avoids the overestimation of landmarks.
引用
收藏
页码：267 / 274
页数：8
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