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Proceedings Paper

Development of standard test methods for unmanned and manned industrial vehicles used near humans
Author(s): Roger Bostelman; Richard Norcross; Joe Falco; Jeremy Marvel
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Paper Abstract

The National Institute of Standards and Technology (NIST) has been researching human-robot-vehicle collaborative environments for automated guided vehicles (AGVs) and manned forklifts. Safety of AGVs and manned vehicles with automated functions (e.g., forklifts that slow/stop automatically in hazardous situations) are the focus of the American National Standards Institute/Industrial Truck Safety Development Foundation (ANSI/ITSDF) B56.5 safety standard. Recently, the NIST Mobile Autonomous Vehicle Obstacle Detection/Avoidance (MAVODA) Project began researching test methods to detect humans or other obstacles entering the vehicle’s path. This causes potential safety hazards in manufacturing facilities where both line-of-sight and non-line-of-sight conditions are prevalent. The test methods described in this paper address both of these conditions. These methods will provide the B56.5 committee with the measurement science basis for sensing systems - both non-contact and contact - that may be used in manufacturing facilities.

Paper Details

Date Published: 29 May 2013
PDF: 15 pages
Proc. SPIE 8756, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2013, 87560P (29 May 2013); doi: 10.1117/12.2019063
Show Author Affiliations
Roger Bostelman, National Institute of Standards and Technology (United States)
Richard Norcross, National Institute of Standards and Technology (United States)
Joe Falco, National Institute of Standards and Technology (United States)
Jeremy Marvel, National Institute of Standards and Technology (United States)


Published in SPIE Proceedings Vol. 8756:
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2013
Jerome J. Braun, Editor(s)

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