{"id":11187,"date":"2017-01-19T18:40:00","date_gmt":"2017-01-19T18:40:00","guid":{"rendered":"https:\/\/lcas.lincoln.ac.uk\/wp\/?page_id=11187"},"modified":"2025-07-03T10:31:06","modified_gmt":"2025-07-03T09:31:06","slug":"ncnr-national-centre-for-nuclear-robotics","status":"publish","type":"page","link":"https:\/\/lcas.lincoln.ac.uk\/wp\/research\/projects\/ncnr-national-centre-for-nuclear-robotics\/","title":{"rendered":"NCNR – National Centre for Nuclear Robotics"},"content":{"rendered":"\n

EPSRC RAI Hub, robotics for extreme environments<\/a>, 2017-2021.<\/em><\/p>\n\n\n

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\"NCNR<\/a><\/figure><\/div>\n\n\n

The National Centre for Nuclear Robotics (NCNR)<\/a> is a multi-disciplinary EPSRC RAI (Robotics and Artificial Intelligence) Hub consisting of most leading nuclear robotics experts in the UK including Universities of Birmingham, Queen Mary, Essex, Bristol, Edinburgh, Lancaster and Lincoln. Under this project, more than 40 postdoctoral researchers and PhD researchers form a team to develop cutting-edge scientific solutions to all aspects of nuclear robotics such as sensor and manipulator design, computer vision, robotic grasping and manipulation, mobile robotics, intuitive user interfaces and shared autonomy.<\/p>\n\n\n\n

At the University of Lincoln, we will develop new machine learning algorithms for several crucial applications in nuclear robotics such as waste handling, cell decommissioning and site monitoring with mobile robots. Clean-up and decommissioning of nuclear waste are one of the biggest challenges for our and the next generations with enormous predicted costs (up to \u00a3200Bn over the next hundred years). Moreover, recent disaster situations such as Fukushima have shown the crucial importance of robotics technology for monitoring and intervention, which is missing up to date. Our team will focus on algorithms for vision-guided robot grasping and manipulation, cutting, shared control and semi-autonomy, mobile robot navigation and outdoor mapping and navigation with a strong focus on machine learning and adaptation techniques. A dedicated bimanual robot arm platform is being developed, mounted on a mobile platform, and to be operated using shared autonomy, teleoperation and augmented reality concepts to be developed.<\/p>\n\n\n