Robot Person Following Under Partial Occlusion
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Robot person following (RPF) is a capability that supports many useful human-robot-interaction (HRI) applications of a mobile robot. However, existing solutions to person following often assume a 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 show that, even under partial occlusion, the proposed method can still locate the person more reliably than the existing methods. In combination with this person location module, our RPF system achieves SOTA results in a public person following dataset. As well, the application of our method is demonstrated in real experiments on a mobile robot.
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