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The Detection and Following of Human Legs Through Inductive Approaches for a Mobile Robot With a Single Laser Range Finder

Woojin Chung, Hoyeon Kim, Yoonkyu Yoo, Chang-bae Moon, Jooyoung Park

Year
2011
Citations
131

Abstract

The human-friendly navigation of mobile robots is a significant social and technological issue. There are many potential applications of human-following technology. Good examples are human-following shopping carts, porter robots at airports, and museum guide robots. In this paper, we propose detection and tracking schemes for human legs by the use of a single laser range finder. The leg detection algorithm takes an inductive approach by the application of a support vector data description scheme and simple attributes. We establish an efficient leg-tracking scheme by exploiting a human walking model to achieve robust tracking under occlusions. The proposed schemes are successfully verified through experiments.

Keywords

RobotMobile robotScheme (mathematics)Computer scienceTracking (education)Artificial intelligenceComputer visionRange (aeronautics)Human–robot interactionEngineering

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