RAICAM · Robotics and Artificial Intelligence for Critical Asset Monitoring

Robotics and Artificial Intelligence for Critical Asset Monitoring

The central scientific goal of RAICAM is to conduct research into the underlying technologies in Robotics and Artificial Intelligence (AI) that will unlock the capability for a fleet of robots to conduct coordinated sampling campaigns in industrial facilities with varying levels of autonomy. The use of robots for the inspection, maintenance, and repair (IMR) of critical infrastructure assets will revolutionise many sectors such as energy generation, energy transmission, civil infrastructure and utilities. In fact, for some industries, the use of robotics is the only way to realise their full potential. For example, offshore wind energy generation is only feasible at the scales required if robotic platforms are used, from a safety, economic and skills shortage perspective. To realise their full potential, robots will need to interact with the environment to perform maintenance and repair activities. Environmental interaction is a highly complex activity requiring a multi-disciplinary approach combining cognition (perception and reasoning), control, planning and, depending on the level of autonomy, human interactions. Whilst human technicians currently conduct sampling regimes, there is often significant uncertainty associated with repeatability, accuracy, and efficacy of the samples. A recent study has shown that automated systems have the potential to outperform humans when collecting samples. Humans are also limited as to where they can take samples from, either due to environmental hazardous (radiation, chemicals, heat) or location (confined spaces or heights). The central scientific goal of RAICAM is to conduct research into the underlying technologies in Robotics and AI that will unlock the capability for a fleet of robots to conduct coordinated sampling campaigns in industrial facilities with varying levels of autonomy. The RAICAM Doctoral Network will train the next generation of robotic systems engineers who will develop creative and innovative multi-disciplinary skills, enhancing their inter-sectoral mobility.

Data: CORDIS, © European Union