• English
  • Deutsch
  • Log In
    or
  • Research Outputs
  • Projects
  • Researchers
  • Institutes
  • Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Water Streak Detection with Convolutional Neural Networks for Scrubber Dryers
 
  • Details
  • Full
Options
2019
  • Konferenzbeitrag

Titel

Water Streak Detection with Convolutional Neural Networks for Scrubber Dryers

Abstract
Avoiding gray water remainders behind wet floor cleaning machines is an essential requirement for safety of passersby and quality of cleaning results. Nevertheless, operators of scrubber dryers frequently do not pay sufficient attention to this aspect and automatic robotic cleaners cannot even sense water leakage. This paper introduces a compact, low-cost, low-energy water streak detection system for the use with existing and new cleaning machines. It comprises a Raspberry Pi with an Intel Movidius Neural Compute Stick, an illumination source, and a camera to observe the floor after cleaning. The paper evaluates six different Convolutional Neural Network (CNN) architectures on a self-recorded water streak data set which contains nearly 43000 images of 59 different floor types. The results show that up to 97% of all water events can be detected at a low false positive rate of only 2.6%. The fastest CNN Squeezenet can process images at a sufficient speed of over 30 Hz on the low-cost hardware such that real applicability in practice is provided. When using an NVidia Jetson Nano as alternative low-cost computing system, five out of the six networks can be operated faster than 30 Hz.
Author(s)
Jost, Uriel
Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA
Bormann, Richard
Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA
Hauptwerk
Computer vision systems. 12th International Conference, ICVS 2019. Proceedings
Project(s)
BakeR
Funder
Bundesministerium für Wirtschaft und Energie BMWi (Deutschland)
Konferenz
International Conference on Computer Vision Systems (ICVS) 2019
DOI
10.1007/978-3-030-34995-0_24
File(s)
N-577842.pdf (2.17 MB)
Language
Englisch
google-scholar
IPA
Tags
  • Sensor

  • Reinigungsroboter

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Send Feedback
© 2022