Robust and precise capture of human motion in difficult production environments using
· Inertial sensor suits (Xsens MVN Link and Awinda)
· Data gloves (Manus Prime II Xsens)
· Eye trackers (Pupil Invisible)
Benefit: Automation of motion capture of workers in production plants
Real-time integration of motion capture in 3D environments with 3D process and resource data and physics simulation (Unity3D)
Benefit: More efficient simulation environments for captured motion in a production context
Automatic delimitation of single motions and assignment of motions to work schedules
Benefit: Reduction in manual analyses which are currently too time-consuming
Generation of AI-based motion models for the simulation of manual assembly processes for reliable planning
Benefit: Faster, more realistic and higher quality planning of manual processes in serial assembly while taking into account workers’ motions
Linking of human and robot motion models
Benefit: Increased safety in human-robot collaboration due to motion forecasts for humans
Co-simulation of PLC, robot control system and human (Unity 3D, ROS)
Benefit: Virtual commissioning requiring less work and no costly special software
Innovative collaboration concepts
Benefit: More effective ways of human-robot collaboration with a high level of acceptance
Resilience measurement
Benefit: Automatisierte Erkennung ungünstigen dynamischen Materialflussverhaltens
Inter-scale effects of reconfigurations in supply chains and shop floors
Benefit: Research on indirect Consequences
Automated planning with AI
Benefit: Increases planning quality and efficiency
The FAMS - Chair of Production Automation and Assembly, University of Siegen is affiliated with the Z-inspection® initiative.
Z-Inspection® is a holistic process for evaluating the trustworthiness of AI-based technologies at different stages of the AI lifecycle. In particular, it focuses on identifying and discussing ethical issues and tensions through the development of socio-technical scenarios.
The process has been published in the IEEE Transactions on Technology and Society. Z-Inspection® is distributed under the terms of the Creative Commons License (Attribution-NonCommercial-ShareAlike CC BY-NC-SA). Z-Inspection® is listed in the new OECD Catalogue of AI Tools & Metrics.
Robust and precise capture of human motion in difficult production environments using
· Inertial sensor suits (Xsens MVN Link and Awinda)
· Data gloves (Manus Prime II Xsens)
· Eye trackers (Pupil Invisible)
Benefit: Automation of motion capture of workers in production plants
Real-time integration of motion capture in 3D environments with 3D process and resource data and physics simulation (Unity3D)
Benefit: More efficient simulation environments for captured motion in a production context
Automatic delimitation of single motions and assignment of motions to work schedules
Benefit: Reduction in manual analyses which are currently too time-consuming
Generation of AI-based motion models for the simulation of manual assembly processes for reliable planning
Benefit: Faster, more realistic and higher quality planning of manual processes in serial assembly while taking into account workers’ motions
Linking of human and robot motion models
Benefit: Increased safety in human-robot collaboration due to motion forecasts for humans
Co-simulation of PLC, robot control system and human (Unity 3D, ROS)
Benefit: Virtual commissioning requiring less work and no costly special software
Innovative collaboration concepts
Benefit: More effective ways of human-robot collaboration with a high level of acceptance
Resilience measurement
Benefit: Automatisierte Erkennung ungünstigen dynamischen Materialflussverhaltens
Inter-scale effects of reconfigurations in supply chains and shop floors
Benefit: Research on indirect Consequences
Automated planning with AI
Benefit: Increases planning quality and efficiency
The FAMS - Chair of Production Automation and Assembly, University of Siegen is affiliated with the Z-inspection® initiative.
Z-Inspection® is a holistic process for evaluating the trustworthiness of AI-based technologies at different stages of the AI lifecycle. In particular, it focuses on identifying and discussing ethical issues and tensions through the development of socio-technical scenarios.
The process has been published in the IEEE Transactions on Technology and Society. Z-Inspection® is distributed under the terms of the Creative Commons License (Attribution-NonCommercial-ShareAlike CC BY-NC-SA). Z-Inspection® is listed in the new OECD Catalogue of AI Tools & Metrics.