A Modular Digital Twinning Framework for Safety Assurance of Collaborative Robotics

Area of Science:

• Robotics
• Cyber-Physical Systems
• Manufacturing Engineering

Background:

• Digital twins are emerging as powerful tools for managing complex robotic processes.
• Ensuring safety in collaborative robotic manufacturing presents significant challenges.
• Existing frameworks may lack modularity and scalability for diverse applications.

Purpose of the Study:

• To present a novel, modular digital twinning framework for investigating safety in collaborative robotic manufacturing.
• To facilitate the creation of mixed environments (Digital Models, Shadows, Twins).
• To standardize communication and physical system representation across hardware platforms.

Main Methods:

• Developed a modular digital twinning framework with scalable representations.
• Integrated tools for safety analysis and control within the framework.
• Applied the framework to an industrial case study for safety assurance of a collaborative robotic process.
• Utilized a supporting validation module and testing strategy for virtual safety assessment.

Main Results:

• Demonstrated the framework's application to an industrial collaborative robotic manufacturing case study.
• Created a digital twin scenario with individual digital twins for manufacturing entities.
• Successfully applied a synthesized safety controller and virtually assessed its safety claims.
• Generated adequate evidence for safety validation through the framework.

Conclusions:

• The developed digital twinning framework is a versatile research tool for robotic safety assurance.
• The framework enables virtual assessment of safety claims in collaborative robotic manufacturing.
• Digital twins offer exciting possibilities for enhancing safety in robotic systems.