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Autonomous dirt detection for cleaning in office environments

 
: Bormann, Richard; Weisshardt, Florian; Arbeiter, Georg; Fischer, Jan

:
Preprint urn:nbn:de:0011-n-2421004 (3.6 MByte PDF)
MD5 Fingerprint: 1faf20ca6f1677f1fe1b4a7af895411e
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Created on: 30.11.2013


IEEE Robotics and Automation Society; Karlsruher Institut für Technologie -KIT-:
IEEE International Conference on Robotics and Automation, ICRA 2013 : Anthropomatics - Technologies for Humans. May 6-10, 2013, Karlsruhe, Germany
New York, NY: IEEE, 2013
ISBN: 978-1-4673-5642-8 (USB Stick)
ISBN: 978-1-4673-5641-1 (Print)
ISBN: 978-1-4673-5643-5
pp.1252-1259
International Conference on Robotics and Automation (ICRA) <2013, Karlsruhe>
Bundesministerium für Wirtschaft und Technologie BMWi
01Ma11005; AutoPnP
English
Conference Paper, Electronic Publication
Fraunhofer IPA ()
Schmutzerkennung; dirt detection; robotic dirt detection; Bodenreinigungsroboter; Cleaning Robot; robotic cleaning; machine vision; maschinelles Sehen; Schmutzdatenbank; Roboter; Reinigen; Bilderkennung; Schmutz

Abstract
The advances of technologies for mobile robotics enable the application of robots to increasingly complex tasks. Cleaning office buildings on a daily basis is a problem that could be partially automatized with a cleaning robot that assists the cleaning professional yielding a higher cleaning capacity. A typical task in this domain is the selective cleaning, that is a focused cleaning effort to dirty spots, which speeds up the overall cleaning procedure significantly. To enable a robotic cleaner to accomplish this task, it is first necessary to distinguish dirty areas from the clean remainder. This paper discusses a vision-based dirt detection system for mobile cleaning robots that can be applied to any surface and dirt without previous training, that is fast enough to be executed on a mobile robot and which achieves high dirt recognition rates of 90% at an acceptable false positive rate of 45%. The paper also introduces a large database of real scenes which was used for the evaluation and is publicly available.

: http://publica.fraunhofer.de/documents/N-242100.html