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Impact Factor:0.181

Affiliation of Author(s):武汉大学

Journal:Wuhan University Journal of Natural Sciences

Place of Publication:湖北省武汉市

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

Abstract: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.

Co-author:Hong Cheng,Zhang Dengyi

First Author:Xu Pei

Indexed by:Article

Correspondence Author:Su Kehua

Document Type:J

Volume:24

Issue:2

Page Number:176-184

ISSN No.:1007-1202

Translation or Not:no

Date of Publication:2019-06-04

Included Journals:SCI