Robotics and Artificial Intelligence for Critical Asset Monitoring
This project aims to develop technologies which will enhance the operational capabilities of mobile robots for use in the inspection and maintenance of industrial facilities. A major task in many industrial environments is the retrieval of samples for chemical or biological analysis. Surface swabbing is often conducted manually, but this creates limits on the number of samples that can be taken and their location. There are often many places that can't be reached by people either due to the location (very high, or in confined/restricted access spaces) or environmental hazardous (such as heat or radiation). This project will develop a multi-domain, multi-agent robotic sample retrieval system that will be able to obtain samples across a range of environments. These samples will either be stored for ex-situ analysis in labs or taken to mobile labs for in-situ, real-time analysed. Due to the nature of the operational environments, full autonomy is not desirable, so shared autonomy (human-in-the-loop) will be required. The primary application focus will be nuclear environments, however the technologies will be applicable to many other sectors include petrochemical, offshore and agriculture.
This project aims to develop technologies which will enhance the operational capabilities of mobile robots for use in the inspection and maintenance of industrial facilities. A major task in many industrial environments is the retrieval of samples for chemical or biological analysis. Surface swabbing is often conducted manually, but this creates limits on the number of samples that can be taken and their location. There are often many places that can't be reached by people either due to the location (very high, or in confined/restricted access spaces) or environmental hazardous (such as heat or radiation). This project will develop a multi-domain, multi-agent robotic sample retrieval system that will be able to obtain samples across a range of environments. These samples will either be stored for ex-situ analysis in labs or taken to mobile labs for in-situ, real-time analysed. Due to the nature of the operational environments, full autonomy is not desirable, so shared autonomy (human-in-the-loop) will be required. The primary application focus will be nuclear environments, however the technologies will be applicable to many other sectors include petrochemical, offshore and agriculture.

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