Summary and overview

The UK has fallen significantly behind other countries when it comes to adopting robotics/automation within factories. Collaborative automation, that works directly with people, offers fantastic opportunities for strengthening UK manufacturing and rebuilding the UK economy. It will enable companies to increase productivity, to be more responsive and resilient when facing external pressures (like the Covid-19 pandemic) to protect jobs and to grow.

To enable confident investment in automation, we need to overcome current fundamental barriers. Automation needs to be easier to set up and use, more capable to deal with complex tasks, more flexible in what it can do, and developed to safely and intuitively collaborate in a way that is welcomed by existing workers and wider society.

Research areas

To overcome these barriers, the ISCF Made Smarter Innovation Research Centre for Smart, Collaborative Industrial Robotics (Smart Cobotics Centre) has worked with industry to identify four priority areas for research:

• collaboration
• autonomy
• simplicity
• acceptance

The initial programme will tackle current fundamental challenges in each of these areas and develop testbeds for demonstration of results. Over the course of the programme, the Smart Cobotics Center will also conduct responsive research, rapidly testing new ideas to solve real world manufacturing automation challenges.

The Centre will create a network of academia and industry, connecting stakeholders, identifying challenges/opportunities, reviewing progress and sharing results. Open access models and data will enable wider academia to further explore the latest scientific advances. Within the manufacturing industry, large enterprises will benefit as automation can be brought.

The Smart Cobotics Centre research programme at Bristol centres on the problem of dextrous manipulation. Our goal is to develop the core physical interaction technologies that will enable a robot to work seamlessly with a human partner, for example to make a cake, to assemble a car or to pick and pack groceries for delivery. All of these tasks can be done by human, but current robots are not able to do them because they lack intelligent and versatile dextrous manipulation skill.

We are developing the soft robot actuation, sensing and gripping technologies, and fusing these with novel machine learning algorithms. Our work is revealing the potential for intelligent dextrous manipulation with soft robotics to bridge the gap between the skilled human and the future robotic coworker.

Co-investigators

• Professor Nathan Lepora
• Professor Kerstin Eder