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Safety standard for mobile robots: a proposal for 3D sensors
School of Technology and Society, University of Skövde, Skövde, Sweden.
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
2011 (English)In: Proceedings of  the 5th European Conference on Mobile Robots, ECMR'2011 / [ed] Achim J. Lilienthal, Tom Duckett, Örebro: Centre for Applied Autonomous Sensor Systems (AASS) , 2011, p. 245-251Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we present a new and uniform way of evaluate 3D sensor performance. It is rare that standardized test specifications are used in research on mobile robots. A test rig with objects in the industrial safety standard Safety of industrial trucks - driverless trucks and their systems EN1525 is extended by thin vertical and horizontal objects that represent a fork on a forklift, a ladder and a hanging cable. A comparison of atrinocular stereo vision system, a 3D TOF (Time- Of-Flight) range camera and a Kinect device is made to verify the use of the test rig. All sensors detect the objects in the safety standard EN1525. The Kinect and 3D TOF camera shows reliable results for the objects in the safety standard at distances up to 5 m. The trinocular system is the only sensor in the test that detects the thin structures. The proposed test rig can be used to evaluate sensors to detect thin structures.

Place, publisher, year, edition, pages
Örebro: Centre for Applied Autonomous Sensor Systems (AASS) , 2011. p. 245-251
Keyword [en]
safety standard for mobile robots, 3D sensors, Trinocular vision, EN1525
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hh:diva-16085OAI: oai:DiVA.org:hh-16085DiVA, id: diva2:438312
Conference
The 5th European Conference on Mobile Robots, ECMR 2011, Örebro, Sweden, September 7-9, 2011
Available from: 2011-09-02 Created: 2011-09-02 Last updated: 2018-03-22Bibliographically 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. p. ix, 80
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: 2018-03-22Bibliographically approved

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Hedenberg, KlasÅstrand, Björn

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