Projects
Active projects
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Robotic skill transfer and augmentation for contact-rich tasks in manufacturing (STAMAN)
Value: £1.3M (FEC) including £1M from the EPSRC
Duration: 2024-2027
STAMAN’s vision is to create AI-based mechanisms to allow robots to share and recreate obtained digital skills (e.g. motion and force/torque control strategies) to allow easy automation scale-up for contact-rich tasks. This includes considering two research questions:
1) For skill transfer – how can a contact-rich skill be quickly transferred to a different robot (e.g. transferring a bolt-nut separation skill from a high-precision robot to a low-precision robot)?
2) For skill augmentation – how can existing contact-rich skills be used to create new contact-rich skills (e.g. augmentation of rigid-material skills to deal with soft materials)?
The project will develop a portfolio of research into the science of digital skills for contact-rich tasks, focusing on common manufacturing tasks such as bolt-nut assembly/disassembly, peg-hole insertion/separation, and shaft-ring assembly/disassembly. The ability to transfer and augment digital skills for contact-rich tasks will allow automation systems to be implemented on a larger scale, with minimal manual setting and fine-tuning required. STAMAN aims to create transferrable and augmentable digital skills that will underpin the development of mass machine skills for future manufacturing, similar to how industrial robots have contributed to modern mass production.
The proposed research encourages more use of robots in assembly (e.g. automotive, aerospace, electronics, etc.) and disassembly (e.g. repairs, remanufacturing and recycling), and thus directly contributes to the UK’s Made Smarter initiative and the circular economy goals.
Details: UKRI
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Self-learning robotics for industrial contact-rich tasks (ATARI): enabling smart learning in automated disassembly
Value: £300k from EPSRC and £100k from the University of Birmingham
Duration: 10/2021-09/2023
This project will develop a self-learning mechanism to allow robots to learn disassembly tasks and the respective control strategies autonomously, by combining multidimensional sensing and machine learning techniques. This capability will help build a more plug-and-play disassembly automation system, and reduce the technical difficulties and the implementation costs of disassembly automation.
It is expected the next generation industrial robotics can be adopted in more complex and uncertain tasks such as maintenance, cleaning, repair, remanufacturing and recycling, where many processes are contact-rich. Disassembly is a typical contact-rich task. The PI envisages that self-learning robotic disassembly will provide key understandings and technologies that can be adopted to the automation of other types of contact-rich tasks in the future to encourage a wider adoption of robots in the UK industry.
Past projects
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Affordable and modular robotic disassembly systems (EPSRC IAA )
Value: EPSRC IAA Follow on rate
Duration: 4/2023-11/2023
and medical equipment, involve significant health and safety risks in disassembly (e.g. leakage and explosion), making disassembly expensive and difficult to scale up.
In this project, we aim to significantly reduce the cost of robotic technologies by improving the design of the disassembly robot system to create a general-use low-cost robotic disassembly robot station (e.g. a single robot cell) that can be used for *** and *** – the two major disassembly operations to disassemble common consumer products.
solutions. Being standardised means the proposed robotic disassembly product can be mass-duplicated and mass-produced which will pave the way for scale-up.
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Hierarchical use of battery : Intelligent evaluation and collaborative robot disassembly
Value: £*** from JITRI
Duration: 10/2019-10/2022
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AMTECAA (Advanced Manufacturing Technologies to Create, Activate & Automate) programme
Value: £10m funded by the European Structural Investment Funds (ESIF)
Duration: 2019-2023
AMTECAA supports SME’s in Birmingham and Solihull. AMTECAA covers six high-impact interrelated technology areas, i.e. additive manufacturing, advanced machining, surface engineering, laser processing, and industrial automation while digital manufacturing (Industry 4.0) is an overreaching enabler for developing new products and processes.
If you’re looking to explore how automation technologies can help you be more productive or provide a competitive edge then please contact us.
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Automatic disassembly replanning for autonomous remanufacturing
Value: £12k from the Royal Society and £12k from NSFC
Duration: 03/2019-03/2022
and adapt frequently. Current industrial robotic techniques, most of which designed for repetitive and structured motions in assembly, do not have the required flexibility for disassembly. The project will facilitate autonomous multi-agent model and optimal replanning to deal with unforeseen changes in
robotic disassembly processes. We expect to produce scientific results relevant to researchers in robotics, modelling & simulation, remanufacturing and recycling. The resultant techniques will promote the flexibility and robustness of robotic disassembly systems, and thus encourage a wider adoption of remanufacturing.