A Design for Improvement of Visual SLAM in Dynamic Environments Using Feature-Point Removal of Moving Persons

Kai Tai Song*, Ching Hao Meng

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

This paper presents a design to improve the robustness of visual SLAM(vSLAM). A processing step of feature-removal is added to the tracking thread of the conventional ORB-SLAM2 algorithm to improve the localization accuracy of a mobile robot in an environment with moving persons. Instance segmentation and motion tracking are intergrated to identify motion state of people in an image. ORB feature points belonging to moving persons are removed for further processing of the vSLAM pipeline. The advantage of this method is that the vSLAM can remove feature points of moving people, while retain those belonging to static people in the environment, which improves the accuracy of robot pose estimation. The improved ORB-SLAM2 algorithm has been implemented in a NVIDIA Xavier embedded system, which is integrated to a mobile robot. In practical robot navigation experiments, the average positioning error of the proposed method is within 4cm for 22.4m travel distance. Compared with conventional ORB-SLAM2, the average accuracy of our vSLAM method improves 97% in a dynamic environment with moving people.

原文English
主出版物標題2023 International Automatic Control Conference, CACS 2023
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9798350306354
DOIs
出版狀態Published - 2023
事件2023 International Automatic Control Conference, CACS 2023 - Penghu, 台灣
持續時間: 26 10月 202329 10月 2023

出版系列

名字2023 International Automatic Control Conference, CACS 2023

Conference

Conference2023 International Automatic Control Conference, CACS 2023
國家/地區台灣
城市Penghu
期間26/10/2329/10/23

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