hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Stereo vision-based collision avoidance
University of Skövde, School of Technology and Society, Skövde, Sweden.
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
2004 (English)In: The 9th Mechatronics Forum International Conference: Conference Proceedings, Ankara: Atılım University , 2004, 259-270 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper investigates whether a stereo vision system based on points of interest is robust enough to detect obstacles for applications like a mobile robot in an industrial environment and for the visually impaired. Points of interest are extracted with a known method, called KLT. Two algorithms to solve the correspondence problem (Sum of Squared Difference and Variance Normalized Correlation) are used and evaluated as well as a combination of the two. An improvement is made if the two algorithms are combined. The tests show that stereo vision based on points of interest only can be used robustly for obstacle detection if there is enough texture on the obstacle. Otherwise too few points of interest on the object are detected and a reliable estimation of the distance to the object cannot be made.

Place, publisher, year, edition, pages
Ankara: Atılım University , 2004. 259-270 p.
Series
Atılım University Publications, 20
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-25344ISBN: 9756707135 ISBN: 9789756707135 OAI: oai:DiVA.org:hh-25344DiVA: diva2:717273
Conference
Mechatronics 2004, 9th Mechatronics Forum International Conference, Ankara, Turkey, Aug. 30 – Sep. 1, 2004
Available from: 2014-05-14 Created: 2014-05-14 Last updated: 2014-06-05Bibliographically approved
In thesis
1. Obstacle Detection for Driverless Trucks in Industrial Environments
Open this publication in new window or tab >>Obstacle Detection for Driverless Trucks in Industrial Environments
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

With an increased demand on productivity and safety in industry, new issues in terms of automated material handling arise. This results in industries not having a homogenous fleet of trucks and driven and driverless trucks are mixed in a dynamic environment. Driven trucks are more flexible than driverless trucks, but are also involved in more accidents. A transition from driven to driverless trucks can increase safety, but also productivity in terms of fewer accidents and more accurate delivery. Hence, reliable and standardized solutions that avoid accidents are important to achieve high productivity and safety. There are two different safety standards for driverless trucks for Europe (EN1525) and U.S. (B56.5–2012) and they have developed differently. In terms of obstacles, they both consider contact with humans. However, a machinery-shaped object has recently been added to the U.S. standard (B56.5–2012). The U.S. standard also considers different materials for different sensors and non-contact sensors. For obstacle detection, the historical contact-sensitive mechanical bumpers as well as the traditional laser scanner used today both have limitations – they do not detect hanging objects. In this work we have identified several thin objects that are of interest in an industrial environment. A test apparatus with a thin structure is introduced for a more uniform way to evaluate sensors. To detect thin obstacles, we used a standard setup of a stereo system and developed this further to a trinocular system (a stereo system with three cameras). We also propose a method to evaluate 3D sensors based on the information from a 2D range sensor. The 3D model is created by measuring the position of a reflector with known position to an object with a known size. The trinocular system, a 3D TOF camera and a Kinect sensor are evaluated with this method. The results showed that the method can be used to evaluate sensors. It also showed that 3D sensor systems have potential to be used on driverless trucks to detect obstacles, initially as a complement to existing safety classed sensors. To improve safety and productivity, there is a need for harmonization of the European and the U.S. safety standards. Furthermore, parallel development of sensor systems and standards is needed to make use of state-of-the-art technology for sensors.

Place, publisher, year, edition, pages
Halmstad: Halmstad University Press, 2014. ix, 80 p.
Series
Halmstad University Dissertations, 7
National Category
Signal Processing
Identifiers
urn:nbn:se:hh:diva-25349 (URN)978-91-87045-14-1 (ISBN)978-91-87045-13-4 (ISBN)
Presentation
2014-09-10, Haldasalen, Visionen, Halmstad University, Kristian IV:s väg 3, Halmstad, 13:15 (English)
Opponent
Supervisors
Available from: 2014-06-05 Created: 2014-05-14 Last updated: 2014-06-24Bibliographically approved

Open Access in DiVA

No full text

Search in DiVA

By author/editor
Hedenberg, KlasBaerveldt, Albert-Jan
By organisation
Halmstad Embedded and Intelligent Systems Research (EIS)
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar

Total: 51 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf