Paper
29 May 2013 Development of standard test methods for unmanned and manned industrial vehicles used near humans
Roger Bostelman, Richard Norcross, Joe Falco, Jeremy Marvel
Author Affiliations +
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.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Roger Bostelman, Richard Norcross, Joe Falco, and Jeremy Marvel "Development of standard test methods for unmanned and manned industrial vehicles used near humans", Proc. SPIE 8756, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2013, 87560P (29 May 2013); https://doi.org/10.1117/12.2019063
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Standards development

Safety

Sensors

Robots

Manufacturing

Injuries

LIDAR

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