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A Visual Leader-Following Approach With a T-D-R Framework for Quadruped Robots

文献类型：期刊论文

作者Pang, Lei2,3; Cao, Zhiqiang2,3; Yu, Junzhi2,4; Guan, Peiyu2,3; Rong, Xuewen1; Chai, Hui1
刊名IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
出版日期2021-04-01
卷号51期号:4页码:2342-2354
ISSN号2168-2216
关键词Visualization Target tracking Mobile robots Correlation Robot kinematics Cameras Detector leader following long-term tracking person re-identification (re-ID) quadruped robot
DOI10.1109/TSMC.2019.2912715
通讯作者Cao, Zhiqiang(zhiqiang.cao@ia.ac.cn)
英文摘要The quadruped robot imitates the motions of four-legged animals with a superior flexibility and adaptability to complex terrains, compared with the wheeled and tracked robots. Its leader-following ability is unique to help a human to accomplish complex tasks in a more convenient way. However, long-term following is severely obstructed due to the high-frequency vibration of the quadruped robot and the unevenness of terrains. To solve this problem, a visual approach under a novel T-D-R framework is proposed. The proposed T-D-R framework is composed of a visual tracker based on correlation filter, a person detector with deep learning, and a person re-identification (re-ID) module. The result of the tracker is verified by the detector to improve tracking performance. Especially, the re-ID module is introduced to handle distractions and occlusion caused by other persons, where the convolutional correlation filter (CCF) is employed to discriminate the leader among multiple persons through recording the appearance information in the long run. By comparing the results of the tracker and the detector as well as their similarity scores with the leader identified by the re-ID module, a stable and real-time tracking of the leader can be guaranteed. Experiments reveal that our approach is effective in handling distractions, appearance changes, and illumination variations. A long-distance experiment on a quadruped robot indicates the validity of the proposed approach.
资助项目863 Program[2015AA042201] ; Beijing Advanced Innovation Center for Intelligent Robots and Systems[2018IRS21] ; National Natural Science Foundation of China[61633017] ; National Natural Science Foundation of China[61633020] ; Key Research and Development Program of Shandong Province[2017CXGC0925] ; Open Foundation of the State Key Laboratory of Management and Control for Complex Systems, CASIA[20170111]
WOS研究方向Automation & Control Systems ; Computer Science
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000631202400027
资助机构863 Program ; 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
源URL[http://ir.ia.ac.cn/handle/173211/44151]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者Cao, Zhiqiang
作者单位1.Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
4.Peking Univ, Coll Engn, Dept Mech & Engn Sci, BIC ESAT,State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
推荐引用方式
GB/T 7714		 Pang, Lei,Cao, Zhiqiang,Yu, Junzhi,et al. A Visual Leader-Following Approach With a T-D-R Framework for Quadruped Robots[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2021,51(4):2342-2354.
APA Pang, Lei,Cao, Zhiqiang,Yu, Junzhi,Guan, Peiyu,Rong, Xuewen,&Chai, Hui.(2021).A Visual Leader-Following Approach With a T-D-R Framework for Quadruped Robots.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,51(4),2342-2354.
MLA Pang, Lei,et al."A Visual Leader-Following Approach With a T-D-R Framework for Quadruped Robots".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 51.4(2021):2342-2354.

入库方式： OAI收割

来源：自动化研究所

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