| EPSRC Reference: |
EP/S001913/1 |
| Title: |
Human Centred Robotics for Next-generation Flexible Manufacturing |
| Principal Investigator: |
Yang, Professor C |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
College of Engineering |
| Organisation: |
Swansea University |
| Scheme: |
EPSRC Fellowship - NHFP |
| Starts: |
29 June 2018 |
Ends: |
16 December 2018 |
Value (£): |
544,518
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| EPSRC Research Topic Classifications: |
| Manufacturing Machine & Plant |
Robotics & Autonomy |
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Summary on Grant Application Form |
The proposed research falls within the field of Robotics and Artificial Intelligence Systems; an area that has enormous potential to provide greater levels of throughput, repeatability, productivity and the introduction of more complex tasks to be carried out in a robot collaboration environment within the UK Manufacturing Sector. The introduction of robots in the production process has undeniable benefits: each robot can replace several human operators, performing repetitive tasks. However, reprogramming and operating robots for production purposes can pose significant challenges for businesses, which could be potential barriers to automation and corporate expansion. For example, each time a robot undertakes a new task it must be reprogrammed. Reprogramming multiple robots can take up to several months and involve the services of a specialist robot programmer. This results in high running costs and suboptimal productivity creating a barrier to the adoption of the technology within the wider manufacturing sector. Similarly, colocation of robots with humans and other machines requires higher levels of cognition, perception and autonomy to assimilate with different user experiences and individual preferences, without interfering with operational schedules.
The research is aimed to address these issues and ensure that robotics are more widely adopted, with the intention of producing software and hardware toolkits that once commercially available will enhance efficiency, reduce costs and facilitate corporate expansion. To achieve this two key approaches will be investigated:
Demonstrable (WS1) - which will develop a new skill transfer interface to teach the robots through body posture, hand gesture and voice commands. It will include (a) a comprehensive human motor skills capture system based on fusion of both physical signals including motion and force and physiological signals of muscle internal activities; (b) a user friendly intuitive teaching interface integrating the skill capture system with mixed reality and voice control, (c) a holistic approach to capture and transfer manipulative skills of arm and hand as coordinated system; and (d) skill generalization mechanism for robots to perform new tasks without additional demonstration.
Collaborative (WS2) - to deliver an intelligent control system for cobots to achieve optimal human-robot cooperation, so that a human's flexibility and creativity can be efficiently integrated with a robot's accuracy and repeatability. This involves (a) a reliable and efficient gesture/posture/voice based communication channel for human co-workers to command the robots easily; (b) improved cobot cooperation skills by embedding human intent perception into robot's control actions, (c) learning strategies to capture individual human co-worker's motion/force pattern for a cobot to provide customized support, and (d) validation in commercially available cobots such as KUKA iiwa and UR5-CBR, together with 3-finger Robotiq gripper and 5-finger Wessling Robotic Hand.
The collective outcome will be innovative, user friendly, technology that permits existing members of the workforce to train robots to undertake new tasks - reducing the cost of outsourcing to one fifth and enabling reprogramming to be completed at a rate that is approximately ten times faster than previous methods. This will have notable economic benefits for distributors of the software and companies as end-users within the manufacturing sector. Not only will existing production lines be more cost effective and profitable but new markets (i.e. customisation and the delivery of new products) will be accessible because of the ability to swiftly reprogram robots for new tasks. Therefore, corporate expansion will be facilitated, via the adoption of digital technology (a priority area for the UK Government), ultimately bolstering the UK Economy.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.swan.ac.uk |