2016
DOI: 10.1108/ir-06-2015-0125
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Human-robot collaboration dynamic impact testing and calibration instrument for disposable robot safety artifacts

Abstract: The Dynamic Impact Testing and Calibration Instrument (DITCI) is a simple instrument with a significant data collection and analysis capability that is used for the testing and calibration of biosimulant human tissue artifacts. These artifacts may be used to measure the severity of injuries caused in the case of a robot impact with a human. In this paper we describe the DITCI adjustable impact and flexible foundation mechanism, which allows the selection of a variety of impact force levels and foundation stiff… Show more

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Cited by 18 publications
(13 citation statements)
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“…139 body dimensions of standing and seated males obtained by traditional anthropometric methods and stereo-photographic techniques were used to derive data corresponding to the effective masses in (Haley 1988). These data are currently used in the force-and pressure-measuring devices intended to carry out human-robot collision-based risk analysis (Dagalakis et al 2016;Huelke and Ottersbach (6)…”
Section: Methods For Acquiring Safety Measuresmentioning
confidence: 99%
See 1 more Smart Citation
“…139 body dimensions of standing and seated males obtained by traditional anthropometric methods and stereo-photographic techniques were used to derive data corresponding to the effective masses in (Haley 1988). These data are currently used in the force-and pressure-measuring devices intended to carry out human-robot collision-based risk analysis (Dagalakis et al 2016;Huelke and Ottersbach (6)…”
Section: Methods For Acquiring Safety Measuresmentioning
confidence: 99%
“…Therefore, there arises a need to quantify contact forces and energy density (energy deposited per area on the human body) in different regions of the human body by an industrial robot system during a HIRC application. Such quantifications are mainly carried out in the following four ways: (1) experimental collision testing using standard automotive crash testing equipment (Haddadin et al 2007(Haddadin et al , 2009), (2) by using sensory test-bed setups with predefined inertial and compliance properties (Dagalakis et al 2016;Matthias et al 2014), (3) simulated crash tests using explicit finite element (FE) solvers and (4) by using models based on the compliant contact force (CCF) modelling approach based on the Hertz contact theory (Park et al 2011;Wassink and Stramigioli 2007).…”
Section: Evaluation Of Safe Human-robot Impact Behaviour During Hircmentioning
confidence: 99%
“…These compression constants corresponding to different body regions are averaged values measured from several human subjects of different genders and anthropometric diversity. These data are currently used in the force- and pressure-measuring devices intended to carry out human–robot collision-based risk analysis (Dagalakis et al 2016 ; Huelke and Ottersbach 2012 ). By integrating ( 7 ) at several points of time during the collision process, the local contact deformation (δ) and the rate of deformation can be calculated, which can subsequently be used to estimate the contact area (A C ) by using the expression ( 12 ) (Johnson 1987 ).…”
Section: Impact Model Between Robot and Human Body Regionsmentioning
confidence: 99%
“…2, the sensor system consists of three layers. The top two layers are called the biosimulant artifact, which consists of disks of biosimulant skin and soft tissue [3]. The bottom layer is the structural sensor.…”
Section: Biosimulant Artifacts With Bottom Sensormentioning
confidence: 99%
“…These testing artifacts will make possible the measurement of forces, pressure and strain when humans and robots come into contact and also the magnitude of injuries caused by robot static and impact pressure. The Dynamic Impact Testing and Calibration Instrument (DITCI) is a simple instrument, with a significant data collection and analysis capability that is used for the testing and calibration of biosimulant human tissue artifacts [3].…”
Section: Introductionmentioning
confidence: 99%