| 基于几何约束的室内动态环境视觉SLAM |
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| 引用本文： | 杨世强,范国豪,白乐乐,赵成,李德信. 基于几何约束的室内动态环境视觉SLAM[J]. 计算机工程与应用, 2021, 57(16): 203-212. DOI: 10.3778/j.issn.1002-8331.2005-0158 |
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| 作者姓名： | 杨世强 范国豪 白乐乐 赵成 李德信 |
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| 作者单位： | 西安理工大学 机械与精密仪器工程学院,西安 710048 |
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| 摘 要： | 同时定位与地图创建(Simultaneous Localization and Mapping,SLAM)作为自主移动机器人的基本功能,近年来已成为机器人领域的研究热点.然而现有视觉SLAM算法大多将外部场景作为静态假设,忽略了环境中运动物体对SLAM系统精度的影响,影响SLAM系统在实际环境中的应用.鉴于此,提出一种...
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| 关 键 词： | 同时定位与地图创建(SLAM) 室内动态环境 ORB-SLAM2 动态检测 |
Geometric Constraint-Based Visual SLAM Under Dynamic Indoor Environment |
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| YANG Shiqiang,FAN Guohao,BAI Lele,ZHAO Cheng,LI Dexin. Geometric Constraint-Based Visual SLAM Under Dynamic Indoor Environment[J]. Computer Engineering and Applications, 2021, 57(16): 203-212. DOI: 10.3778/j.issn.1002-8331.2005-0158 |
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| Authors: | YANG Shiqiang FAN Guohao BAI Lele ZHAO Cheng LI Dexin |
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| Affiliation: | School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China |
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| Abstract: | As a basic function of autonomous mobile robots, Simultaneous Localization and Mapping（SLAM） has been widely researched in recent years. However, most state-of-art visual SLAMs adopt a strong scene rigidity assumption for analytical convenience, which limits the utility of these algorithms for real-world environments with independent dynamic objects. This paper presents a robust visual SLAM towards dynamic indoor scenes, which is built on the RGB-D mode of ORB-SLAM2. A dynamic detection method based on geometric constraints is added to the front end of ORB-SLAM2. First, the dynamic features in the scene are coarsely filtered using a geometric constraint method. Then the remaining features are used as sample points for the improved Random Sample Consensus（RANSAC） algorithm to estimate the stable fundamental matrix. And the epipolar geometry is used to filter out the real dynamic features in the scene. Experiments on the public TUM RGB-D dataset are conducted to evaluate the proposed approach. This evaluation reveals that the proposed algorithm can effectively improve the positioning accuracy of the ORB-SLAM2 system in high-dynamic scenarios. |
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| Keywords: | Simultaneous Localization and Mapping（SLAM） dynamic indoor environment ORB-SLAM2 dynamic detection |
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