Robot Person Following Under Partial Occlusion

• Main Authors: Ye, Hanjing, Zhao, Jieting, Pan, Yaling, Chen, Weinan, He, Li, Zhang, Hong
• Format: Journal Article
• Language: English
• Published: 04-02-2023
• Subjects: Computer Science - Robotics
• DOI: 10.48550/arxiv.2302.02121

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.