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Using Physics-based Digital Twins and Extended Reality for the Safety and Ergonomics Evaluation of Cobotic workstations

Vincent Weistroffer 1, * Francois Keith 1 Arnaud Bisiaux 1 Claude Andriot 1 Antoine Lasnier 2 
* Corresponding author
1 LSI - Laboratoire Simulation Interactive
DIASI - Département Intelligence Ambiante et Systèmes Interactifs : DRT/LIST/DIASI
Abstract : Cobotic workstations in industrial plants involve a new kind of collaborative robots that can interact with operators. These cobots enable more flexibility and they can reduce the cycle time and the floor space of the workstation. However, cobots also introduce new safety concerns with regard to operators, and they may have an impact on the workstation ergonomics. For those reasons, introducing cobots in a workstation always require additional studies on safety and ergonomics before being applied and certified. Certification rules are often complex to understand. We present the SEEROB framework for the Safety and Ergonomics Evaluation of ROBotic workstations. The SEEROB framework simulates a physics-based digital twin of the cobotic workstation and computes a large panel of criteria used for safety and ergonomics. These criteria may be processed for the certification of the workstation. The SEEROB framework also uses extended reality technologies to display the digital twin and its associated data: users can use virtual reality headsets for the design of non-existing workstations, and mixed reality devices to better understand safety and ergonomics constraints on existing workstations. The SEEROB framework was tested on various laboratory and industrial use cases, involving different kinds of robots.
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Submitted on : Friday, February 18, 2022 - 12:04:06 PM
Last modification on : Wednesday, February 23, 2022 - 3:30:42 AM
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Vincent Weistroffer, Francois Keith, Arnaud Bisiaux, Claude Andriot, Antoine Lasnier. Using Physics-based Digital Twins and Extended Reality for the Safety and Ergonomics Evaluation of Cobotic workstations. Frontiers in Virtual Reality, Frontiers, 2022, 3, https://doi.org/10.3389/frvir.2022.781830. ⟨10.3389/frvir.2022.781830⟩. ⟨cea-03579852⟩

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