Removing the cage and curtains: how can we assure the safety of cobots to support increased productivity in manufacturing?

The CSI:Cobot project demonstrated how research in the fields of safety engineering, machine learning, and cybersecurity can be applied to human-robot collaborative processes to address safety concerns and improve confidence. The project was undertaken in collaboration with regulators, standards communities, and industrial stakeholders, to ensure relevance to future industrial application.

Contact us

Assuring Autonomy International Programme
+44 (0)1904 325345
Institute for Safe Autonomy, University of York, Deramore Lane, York YO10 5GH

Illustration of a human and cobot working side by side

Project report

The full project report report summarises the approaches and findings of the CSI:Cobot project

Final project report

The challenge

Safety and trust issues hinder the deployment of collaborative robots (cobots) in manufacturing. This project considered how novel safety techniques can be applied to build confidence in the deployment of uncaged cobot systems operating in spaces shared with humans and how such increasingly mobile systems could be regulated. 

The research

The project used two case studies, placing specific emphasis on digital twins for safety analysis, machine learning for vision-based proximity detection, synthesis of safety controllers, testing approaches for analysis of hazards, and security policy, user authentication, and intrusion detection.

In the last phase of the project, the team worked with the Health and Safety Executive to move their methods towards industrial application and shape regulatory change in relation to the use of novel approaches to robot safety.

The results

The key technical outcomes of the project are:

  • development of a modular digital twinning framework for robotics, including tools for safety analysis and visualisation
  • an approach to visual detection and tracking of humans and robots using Region Based Convolutional Neural Networks
  • stochastic modelling and controller synthesis methods to enable dynamic switching between safe robot operation modes
  • application of manual (STPA) and semi-automated (SASSI) techniques to analyse hazards in the system and validate safety controllers
  • threat modelling and identification of security policy/requirements for collaborative systems.
  • development of methods for intrusion detection and continuous user authentication
  • virtual and physical demonstrations of collaborative robot safety techniques

Additionally, through engagement with the HSE (the regulator for industrial robot safety), the project increased understanding of research practice within the HSE , sharing of information to support future regulatory decision making, and shaping of research developments toward regulatory approval.

The project team also ran a three-day Manufacturing Robotics Challenge, including training in safety assurance and robotics, for 38 early-career researchers based in 11 countries.

How can we help regulatory organisations keep pace with technology developments?

Find out more from project PI Dr James Law

Project partners

And for the second phase of the project working with:

Contact us

Assuring Autonomy International Programme
+44 (0)1904 325345
Institute for Safe Autonomy, University of York, Deramore Lane, York YO10 5GH