High-accuracy robotic system for precise object manipulation (HARISOM)

The use of industrial robots, specifically multi-axis robotic systems, for object handling and manipulation has significantly increased due to the need to reduce costs, increase production efficiency and avoid difficult and dangerous jobs for humans. Despite the important capabilities of robots, especially in manufacturing, and their use in many types of process automation, their accuracy is relatively poor (in the millimetre range for 1 m^3 working volume), compared to other Cartesian-based Numerically Controlled (NC) automation systems, due to their joint compliance and relatively high structural flexibility in comparison to load capacity. Because of these limitations, robots are restricted in their use for processes that require very high accuracy. Recently, collaborative robots, a special type of multi-axis industrial robot, that can be placed without a safety fence, have become a popular choice due to their flexibility, simplicity to re-program and ability to safely work collaboratively with humans in the same workplace. The joint compliance in these collaborative robots is even less rigid than traditional industrial robots due to the need to have responsive force sensing and coalition-reaction capabilities, further decreasing accuracy capabilities. Most collaborative robots are unable to achieve an absolute positioning accuracy within a 1 m^3 working volume of less than 2.5 mm, making their accuracy more than one order of magnitude higher than their resolution (0.1 mm). This low accuracy limits their utilisation, especially for collaborative robot, so that they are generally restricted to simple pick-and-place tasks. This project will increase by an order of magnitude the absolute positioning accuracy of industrial robots with multi-axis motion to less than 100 micrometres for working volumes exceeding 1 m^3. In this way we will enable precise object manipulation across many application areas.

Academic: This research project will produce novel research outputs for at least sixteen publications in high-impact journals and papers in leading conferences in the field. In addition, the outputs will also contribute to the development of new manufacturing processes for the handling of rigid and biomaterials. We will also collaborate with researchers at other universities in the UK (Universities of Bath and Nottingham) and international organizations (CERN).

Social: The project will work with an SME partner Nuvision Biotherapies Ltd to solve challenges associated with the preparation amnion biomaterial. The end product of which is used to treat wounds and increase the healing process. The ability to produce this product efficiently will significantly impact healthcare.

Industrial: We will produce a framework for use of our research with industrial robots, including collaborative robots, to increase by an order of magnitude the absolute positioning accuracy of industrial robots. This will enable precise object manipulation across many application areas that will be explored by links contained within the AMRC; and University of Nottingham Manufacturing Metrology Team and Nottingham Advanced Robotics Laboratory.

Teaching: Scientific outputs from the project will be integrated into existing classes on robotics (applications and dynamics); flexible manufacture courses (precision assembly and use of digital technologies); and Machine Learning (Bayesian-based learning process for various applications including object tracking). Enabled through D Branson's position as Manufacturing Engineering Course Director Position.

Commercial: All new developed methods and instruments will be exploited for IP protection through various methods in collaboration with the University of Nottingham Technology Transfer Office and industry project partners.

Skills: The project will employ a number of undergraduate and 6th form summer placement students to provide valuable real-world experience; and further provide teaching material on the development of digital skills training for SMEs and the Manufacturing Engineering Course at the University of Nottingham.