Abstract
We present an ample description of a socially compliant mobile robotic platform, which is developed in the EU-funded project SPENCER. The purpose of this robot is to assist, inform and guide passengers in large and busy airports. One particular aim is to bring travelers of connecting flights conveniently and efficiently from their arrival gate to the passport control. The uniqueness of the project stems from the strong demand of service robots for this application with a large potential impact for the aviation industry on one side, and on the other side from the scientific advancements in social robotics, brought forward and achieved in SPENCER. The main contributions of SPENCER are novel methods to perceive, learn, and model human social behavior and to use this knowledge to plan appropriate actions in realtime for mobile platforms. In this paper, we describe how the project advances the fields of detection and tracking of individuals and groups, recognition of human social relations and activities, normative human behavior learning, socially-aware task and motion planning, learning socially annotated maps, and conducting empirical
experiments to assess socio-psychological effects of normative robot behaviors.
Original language | English |
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Title of host publication | Proceedings of the 10th Conference on Field and Service Robotics, FSR 2015 |
Place of Publication | London |
Publisher | Springer |
Pages | 607-622 |
Number of pages | 14 |
ISBN (Print) | 978-3-319-27700-4 |
DOIs | |
Publication status | Published - 24 Jun 2015 |
Event | 10th Conference on Field and Service Robotics, FSR 2015 - Toronto, Canada Duration: 24 Jun 2015 → 26 Jun 2015 Conference number: 10 |
Publication series
Name | Springer Tracts in Advanced Robotics |
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Publisher | Springer Verlag |
Volume | 113 |
ISSN (Print) | 1610-7438 |
Conference
Conference | 10th Conference on Field and Service Robotics, FSR 2015 |
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Abbreviated title | FSR |
Country/Territory | Canada |
City | Toronto |
Period | 24/06/15 → 26/06/15 |
Keywords
- HMI-HF: Human Factors
- EC Grant Agreement nr.: FP7/600877
- EC Grant Agreement nr.: FP7/2007-2013