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3D Sensors on Driverless Trucks for Detection of Overhanging Objects in the Pathway
Skövde University, Skövde, Sweden.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
2015 (English)In: Autonomous Industrial Vehicles: From the Laboratory to the Factory Floor / [ed] Roger Bostelman & Elena Messina, Conshohocken: ASTM International, 2015, 41-56 p.Chapter in book (Refereed)
Abstract [en]

Human-operated and driverless trucks often collaborate in a mixed work space in industries and warehouses. This is more efficient and flexible than using only one kind of truck. However, since driverless trucks need to give way to trucks, a reliable detection system is required. Several challenges exist in the development of an obstacle detection system in an industrial setting. The first is to select interesting situations and objects. Overhanging objects are often found in industrial environments, e.g. tines on a forklift. Second is choosing a detection system that has the ability to detect those situations. The traditional laser scanner situated two decimetres above the floor does not detect overhanging objects. Third is to ensure that the perception system is reliable. A solution used on trucks today is to mount a 2D laser scanner on the top of the truck and tilt the scanner towards the floor. However, objects at the top of the truck will be detected too late and a collision cannot always be avoided. Our aim is to replace the upper 2D laser scanner with a 3D camera, structural light or time-of-flight (TOF) camera. It is important to maximize the field of view in the desired detection volume. Hence, the placement of the sensor is important. We conducted laboratory experiments to check and compare the various sensors’ capabilities for different colors, used tines and a model of a tine in a controlled industrial environment. We also conducted field experiments in a warehouse. The conclusion is that both the tested structural light and TOF sensors have problems to detect black items that is nonperpendicular to the sensor and at the distance of interest. It is important to optimize the light economy, meaning the illumination power, field of view and exposure time in order to detect as many different objects as possible. Copyright © 2016 by ASTM International

Place, publisher, year, edition, pages
Conshohocken: ASTM International, 2015. 41-56 p.
, ASTM Special Technical Publication, ISSN 0066-0558 ; 1594
Keyword [en]
mobile robots, safety, obstacle detection
National Category
Signal Processing
URN: urn:nbn:se:hh:diva-29358DOI: 10.1520/STP159420150051ISI: 000380525000003ScopusID: 2-s2.0-84978164198ISBN: 9780803176331ISBN: 9780803176348OAI: diva2:850813
ICRA 2015 Workshop on Autonomous Industrial Vehicles: From the Laboratory to the Factory Floor, Seattle, WA, USA, 30 May, 2015
Knowledge Foundation

Conference: Workshop on Autonomous Industrial Vehicles - from Laboratory to the Factory Floor, Seattle, WA, United States, May 26-30, 2015

Available from: 2015-09-02 Created: 2015-09-02 Last updated: 2016-09-22Bibliographically approved

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Åstrand, Björn
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