.png){kind=icon}
返回
CEB-Map: Visual Localization Error Prediction for Safe Navigation
.png){kind=icon}
PRE
AI
DOI：10.1109/JSEN.2020.2999641.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
For safe visual navigation, areas with high localization errors should be concentrated and could be further refined by additional mapping operations. Given an environment map, we propose to predict the visual localization error and hence to either improve the navigation performance or call an additional mapping to refine the built map. Previous work adopts the uncertainty of landmarks for the error prediction. In our work, we take into account both the spatial distribution of visual landmarks and the uncertainty of landmarks. Our main idea is that standing at one place, a good spatial distribution of landmarks means a sufficient enough visible landmarks from all views at that place, i.e., enough landmarks under arbitrary view-direction. Combining the spatial distribution and the uncertainty of landmarks, we propose a new framework to predict the error of visual localization. Furthermore, we show that additional mapping in the area with high predicted error can significantly improve the visual localization precision. Experimental results show that there is a strong relationship between the predicted error and the real error, of which the absolute value of correlation coefficient is between 0.707 to 0.915. We apply our method to conduct an optimal refining policy on the built map and the experimental results show the improved localization precision. Applications on navigation test verify the superiority of our proposed method.
Keyword:
Visualization
Navigation
Uncertainty
Sensors
Estimation
Graphical models
Distribution functions
Visual localization
error prediction
safe navigation
map refining
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}
分享收藏The Association of Urothelial Atypism with Neoplasia: Its Importance in Treatment and Prognosis
PREAI
分享收藏
查看更多内容