Robot Person Following Under Partial Occlusion

Hanjing Ye1; Jieting Zhao1; Yaling Pan2; Weinan Cherr2; Li He1; Hong Zhang1

10.1109/ICRA48891.2023.10160738

2023-05-29

IEEE International Conference on Robotics and Automation (ICRA)

1050-4729

2577-087X

979-8-3503-2366-5

2023 IEEE International Conference on Robotics and Automation (ICRA)

2023-May

7591-7597

29 May-2 June 2023

London, United Kingdom

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Robot person following (RPF) is a capability that supports many useful human-robot-interaction (HRI) applications. However, existing solutions to person following often assume full observation of the tracked person. As a consequence, they cannot track the person reliably under partial occlusion where the assumption of full observation is not satisfied. In this paper, we focus on the problem of robot person following under partial occlusion caused by a limited field of view of a monocular camera. Based on the key insight that it is possible to locate the target person when one or more of his/her joints are visible, we propose a method in which each visible joint contributes a location estimate of the followed person. Experiments on a public person-following dataset show that, even under partial occlusion, the proposed method can still locate the person more reliably than the existing SOTA methods. As well, the application of our method is demonstrated in real experiments on a mobile robot.

Measurement Target tracking Automation Robot vision systems Human-robot interaction Cameras Neck

第一

英语

CPCI-S ; EI

Pearl River Talent Recruitment Program[2019QN01X761] ; National Natural Science Foundation of China[62103179]

Automation & Control Systems ; Computer Science ; Engineering ; Robotics

Automation & Control Systems ; Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Robotics

WOS:001048371100083

20233514633099

Man machine systems

Robotics:731.5

IEEE

1.Department of Electronic and Electrical Engineering, Shenzhen Key Laboratory of Robotics and Computer Vision, Southern University of Science and Technology (SUSTech), SUSTech
2.Biomimetic and Intelligent Robotics Lab, Guangdong University of Technology

Hanjing Ye,Jieting Zhao,Yaling Pan,et al. Robot Person Following Under Partial Occlusion[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:7591-7597.