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Collision Tests in Human-Robot Collaboration: Experiments on the Influence of Additional Impact Parameters on Safety

Clara Fischer, Michael Neuhold, Martin Steiner, Thomas Haspl, Michael Rathmair, Sebastian Schlund

Year
2023
Citations
12
Access
Open access

Abstract

Human-robot collaborations are among the most promising but challenging applications for human-centered production, as both agents involved share a mutual workspace without physical barriers. Safety aspects require limiting the power and force of operations to comply with biomechanical limits in case of a collision according to the International Organization for Standardization (ISO) technical specification ISO/TS 15066:2016. This analysis requires highly elaborate physical crash tests of potential impact scenarios. Formal verification will save considerable amounts of time and effort. However, the equations presented in current guidelines need to be more accurate as many factors influencing the impact force and pressure are not considered, making these equations impractical for the evaluation of real applications. To answer the question of which parameters influence a human-robot collision, we have experimentally analyzed different collision scenarios in various configurations. The main results show the correlation of impactor geometries, edges versus rounding, and Shore hardness of the affected body region that simulates human tissue. This work presents the parameters that a formal human-robot collision verification model should contain, based on experimental tests. Furthermore, a model that identifies a collision’s worst-case impacted body region is introduced. The results of this work will help in simplifying and accelerating the safety evaluation process of collaborative human-robot applications to better realize their potential.

Keywords

CollisionComputer scienceHuman–robot interactionRobotCollision avoidanceHuman–computer interactionSimulationArtificial intelligenceComputer security

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