影响因子：

0.181

所属单位：

武汉大学

发表刊物：

Wuhan University Journal of Natural Sciences

刊物所在地：

湖北省武汉市

关键字：

simultaneous localization and mapping;Project Tango;loop closure detection;visual vocabulary;graph optimization

摘要：

Aiming at the problem of system error and noise in simultaneous localization and mapping (SLAM) technology, we propose a calibration model based on Project Tango device and a loop closure detection algorithm based on visual vocabulary with memory management. The graph optimization is also combined to achieve a running application. First, the color image and depth information of the environment are collected to establish the calibration model of system error and noise. Second, with constraint condition provided by loop closure detection algorithm, speed up robust feature is calculated and matched. Finally, the motion pose model is solved, and the optimal scene model is determined by graph optimization method. This method is compared with Open Constructor for reconstruction on several experimental scenarios. The results show the number of model's points and faces are larger than Open Constructor's, and the scanning time is less than Open Constructor's. The experimental results show the feasibility and efficiency of the proposed algorithm.

合写作者：

Hong Cheng,Zhang Dengyi

第一作者：

Xu Pei

论文类型：

文章

通讯作者：

Su Kehua

文献类型：

J

卷号：

24

期号：

2

页面范围：

176-184

ISSN号：

1007-1202

是否译文：

否

发表时间：

2019-06-04

收录刊物：

SCI