.png){kind=icon}
返回
Indirect Visual Simultaneous Localization and Mapping Based on Linear Models
.png){kind=icon}
PRE
AI
DOI：10.1109/JSEN.2019.2952722.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper proposes an indirect visual simultaneous localization and mapping (V-SLAM) for large-scale outdoor environments based on linear models. With the scale-invariant feature transform (SIFT) algorithm, a design combining key-frame insertion and map management is proposed to avoid redundant computation and unreliable landmarks. Then, an iterative linear equation is employed to update landmarks. With the supplement of reliable map data, absolute camera poses can be obtained using a simple linear equation based on a linearity index. In addition, a linear model helps the system to detect candidates of looped frames and discard invalid loops by means of an outlier weight function. If a loop is detected, an improved trajectory bending algorithm is introduced to optimize the estimations of poses and landmarks. To evaluate the effectiveness of the proposed approach, extensive experiments are conducted using various sequences from a well-known public dataset. Experimental results show that the proposed V-SLAM outperforms other existing methods in terms of various metrics.
Keyword:
Visual simultaneous localization and mapping
indirect method
localization
map building
loop closure
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.5
论文数:
2.1W
被引数:
7.3W
机构
引用论文
.png){kind=icon}
Monuments of Historical Trauma as Sites of Artistic Expression, Emotional Processing and Political Negotiation历史创伤纪念碑作为艺术表达、情感处理和政治协商的场所
PREAI
分享收藏
查看更多内容