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IET Cyber-Systems and Robotics
IET Cyber-Systems and Robotics  2021, Vol. 3 Issue (4): 281-291    DOI: 10.1049/csy2.12019
    
RGB-D SLAM with moving object tracking in dynamic environments
RGB-D SLAM with moving object tracking in dynamic environments
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摘要： Simultaneous localization and mapping methods are fundamental to many robotic applications. In dynamic environments, SLAM methods focus on eliminating the influence of moving objects to construct a static map since they assume a static world. To improve localization robustness in dynamic environments, an RGB-D SLAM method is proposed to build a complete 3D map containing both static and dynamic maps, the latter of which consists of the trajectories and points of the moving objects. Without any prior knowledge of the moving targets, the proposed method uses only the correlation between map points to discriminate between the static scene and the moving objects. After the static points are determined, camera motion estimation is performed only on reliable static map points to eliminate the influence of moving objects. The motion of the moving objects will then be estimated with the obtained camera motion by tracking their dynamic points in subsequent frames. Moreover, multiple groups of dynamic points that belong to the same moving object are fused by a volume overlap checking step. Experimental results are presented to demonstrate the feasibility and performance of the proposed method.
Abstract: Simultaneous localization and mapping methods are fundamental to many robotic applications. In dynamic environments, SLAM methods focus on eliminating the influence of moving objects to construct a static map since they assume a static world. To improve localization robustness in dynamic environments, an RGB-D SLAM method is proposed to build a complete 3D map containing both static and dynamic maps, the latter of which consists of the trajectories and points of the moving objects. Without any prior knowledge of the moving targets, the proposed method uses only the correlation between map points to discriminate between the static scene and the moving objects. After the static points are determined, camera motion estimation is performed only on reliable static map points to eliminate the influence of moving objects. The motion of the moving objects will then be estimated with the obtained camera motion by tracking their dynamic points in subsequent frames. Moreover, multiple groups of dynamic points that belong to the same moving object are fused by a volume overlap checking step. Experimental results are presented to demonstrate the feasibility and performance of the proposed method.
出版日期: 2021-05-12
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作者相关文章　　
Weichen Dai
Yu Zhang
Yuxin Zheng
Donglei Sun
Ping Li

引用本文:

Weichen Dai, Yu Zhang, Yuxin Zheng, Donglei Sun, Ping Li. RGB-D SLAM with moving object tracking in dynamic environments. IET Cyber-Systems and Robotics, 2021, 3(4): 281-291.

链接本文:

https://www.zjujournals.com/iet-csr/CN/10.1049/csy2.12019    或    https://www.zjujournals.com/iet-csr/CN/Y2021/V3/I4/281

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