A Robust Visual Person-Following Approach for Mobile Robots in Disturbing Environments | |
Pang, Lei1,2; Cao, Zhiqiang1,2; Yu, Junzhi1,3; Guan, Peiyu1,2; Chen, Xuechao4,5; Zhang, Weimin4,5 | |
发表期刊 | IEEE SYSTEMS JOURNAL |
ISSN | 1932-8184 |
2020-06-01 | |
卷号 | 14期号:2页码:2965-2968 |
摘要 | This article proposes a robust visual following approach with a deep learning-based person detector, a Kalman filter (KF), and a reidentification module. The KF is introduced to predict the position of the target person, and its state is updated by the associated detection result. To deal with severe distractions and even full occlusion, the reidentification module with an identification model, a verification model, and an appearance gallery is employed in multi-person disturbing environments. Without any customized markers, the proposed approach can follow the target person steadily, and it is robust to occlusion and posture changes of the target person. Experiments results validate the effectiveness of the proposed approach. |
关键词 | Mobile robots Detectors Cameras Visualization Robot vision systems Kalman filter (KF) mobile robot person detector person-following reidentification |
DOI | 10.1109/JSYST.2019.2942953 |
关键词[WOS] | TRACKING |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Beijing Advanced Innovation Center for Intelligent Robots and Systems[2018IRS21] ; National Natural Science Foundation of China[61633017] ; National Natural Science Foundation of China[61633020] ; National Natural Science Foundation of China[61836015] ; Key Research and Development Program of Shandong Province[2017CXGC0925] ; Open Foundation of the State Key Laboratory of Management and Control for Complex Systems, CASIA[20190106] |
项目资助者 | Beijing Advanced Innovation Center for Intelligent Robots and Systems ; National Natural Science Foundation of China ; Key Research and Development Program of Shandong Province ; Open Foundation of the State Key Laboratory of Management and Control for Complex Systems, CASIA |
WOS研究方向 | Computer Science ; Engineering ; Operations Research & Management Science ; Telecommunications |
WOS类目 | Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Operations Research & Management Science ; Telecommunications |
WOS记录号 | WOS:000543049900134 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39922 |
专题 | 复杂系统管理与控制国家重点实验室_先进机器人 |
通讯作者 | Cao, Zhiqiang |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Peking Univ, Coll Engn, State Key Lab Turbulence & Complex Syst, BIC ESAr,Dept Mech & Engn Sci, Beijing 100871, Peoples R China 4.Beijing Adv Innovat Ctr Intelligent Robots & Syst, Beijing 100081, Peoples R China 5.Beijing Inst Technol, Intelligent Robot Inst, Beijing 100081, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Pang, Lei,Cao, Zhiqiang,Yu, Junzhi,et al. A Robust Visual Person-Following Approach for Mobile Robots in Disturbing Environments[J]. IEEE SYSTEMS JOURNAL,2020,14(2):2965-2968. |
APA | Pang, Lei,Cao, Zhiqiang,Yu, Junzhi,Guan, Peiyu,Chen, Xuechao,&Zhang, Weimin.(2020).A Robust Visual Person-Following Approach for Mobile Robots in Disturbing Environments.IEEE SYSTEMS JOURNAL,14(2),2965-2968. |
MLA | Pang, Lei,et al."A Robust Visual Person-Following Approach for Mobile Robots in Disturbing Environments".IEEE SYSTEMS JOURNAL 14.2(2020):2965-2968. |
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