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Learning Robot Vision for Assisted Living
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Author(s): Wenjie Yan (University of Hamburg, Germany), Elena Torta (Eindhoven University of Technology, The Netherlands), David van der Pol (Eindhoven University of Technology, The Netherlands), Nils Meins (University of Hamburg, Germany), Cornelius Weber (University of Hamburg, Germany), Raymond H. Cuijpers (Eindhoven University of Technology, The Netherlands)and Stefan Wermter (University of Hamburg, Germany)
Copyright: 2013
Pages: 24
Source title:
Image Processing: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-3994-2.ch062
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Abstract
This chapter presents an overview of a typical scenario of Ambient Assisted Living (AAL) in which a robot navigates to a person for conveying information. Indoor robot navigation is a challenging task due to the complexity of real-home environments and the need of online learning abilities to adjust for dynamic conditions. A comparison between systems with different sensor typologies shows that vision-based systems promise to provide good performance and a wide scope of usage at reasonable cost. Moreover, vision-based systems can perform different tasks simultaneously by applying different algorithms to the input data stream thus enhancing the flexibility of the system. The authors introduce the state of the art of several computer vision methods for realizing indoor robotic navigation to a person and human-robot interaction. A case study has been conducted in which a robot, which is part of an AAL system, navigates to a person and interacts with her. The authors evaluate this test case and give an outlook on the potential of learning robot vision in ambient homes.
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