.png){kind=icon}
返回
3D LiDAR-Based Global Localization Using Siamese Neural Network
.png){kind=icon}
PRE
AI
DOI：10.1109/TITS.2019.2905046.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Global localization in 3D point clouds is a challenging task for mobile vehicles in outdoor scenarios, which requires the vehicle to localize itself correctly in a given map without prior knowledge of its pose. This is a critical component of autonomous vehicles or robots on the road for handling localization failures. In this paper, based on reduced dimension scan representations learned from neural networks, a solution to global localization is proposed by achieving place recognition first and then metric pose estimation in the global prior map. Specifically, we present a semi-handcrafted feature learning method for 3D Light detection and ranging (LiDAR) point clouds using artificial statistics and siamese network, which transforms the place recognition problem into a similarity modeling problem. Additionally, the sensor data using dimension reduced representations require less storage space and make the searching easier. With the learned representations by networks and the global poses, a prior map is built and used in the localization framework. In the localization step, position only observations obtained by place recognition are used in a particle filter algorithm to achieve precise pose estimation. To demonstrate the effectiveness of our place recognition and localization approach, KITTI benchmark and our multi-session datasets are employed for comparison with other geometric-based algorithms. The results show that our system can achieve both high accuracy and efficiency for long-term autonomy.
Keyword:
Three-dimensional displays
Laser radar
Pose estimation
Neural networks
Task analysis
Robot sensing systems
Measurement
Mobile vehicles
place recognition
siamese network
global localization
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:
8.4
论文数:
9.7K
被引数:
6.3W
机构
引用论文
Subversion of Autophagy in Adherent Invasive Escherichia coli-Infected Neutrophils Induces Inflammation and Cell Death.png)
PLoS ONE
OAAI
PLoS ONEIF0
OAAI分享收藏
Mutations in KaiA, a clock protein, extend the period of circadian rhythm in the cyanobacterium Synechococcus elongatus PCC 7942MicrobiologyOAAI
MicrobiologyIF0
OAAI分享收藏
查看更多内容