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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.
Roger Bostelman,Richard Norcross,Joe Falco, andJeremy 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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Roger Bostelman, Richard Norcross, Joe Falco, 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