Projects per year
Abstract
Nuclear facilities can often require continuous monitoring to ensure there is no contamination of radioactive materials that might lead to safety or environmental issues. The current approach to radiological monitoring is to use human operators, which is both time consuming and cost inefficient, and as with many repetitive, routine tasks, there are considerable opportunities for the process to be improved through the utilization of autonomous robotic systems. This paper describes the design and development of an autonomous, ground based radiological monitoring robot, Continuous Autonomous Radiation Monitoring Assistance (CARMA) and how it was able to detect and locate a fixed a source that was embedded into the floor when it was deployed into an active
area on the Sellafield nuclear site. This deployment was the first time that a fully autonomous robot had ever been deployed at Sellafield, the largest nuclear site in Europe.
area on the Sellafield nuclear site. This deployment was the first time that a fully autonomous robot had ever been deployed at Sellafield, the largest nuclear site in Europe.
Original language | English |
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Article number | 8574974 |
Pages (from-to) | 35-43 |
Number of pages | 9 |
Journal | IEEE Robotics and Automation Magazine |
Volume | 26 |
Issue number | 1 |
Early online date | 13 Dec 2018 |
DOIs | |
Publication status | Published - 1 Mar 2019 |
Research Beacons, Institutes and Platforms
- Dalton Nuclear Institute
Fingerprint
Dive into the research topics of 'A robot to monitor nuclear facilities: Using autonomous radiation-monitoring assistance to reduce risk and cost'. Together they form a unique fingerprint.Projects
- 1 Finished
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Robotics and Artificial Intelligence for Nuclear (RAIN)
Lennox, B. (PI), Arvin, F. (CoI), Brown, G. (CoI), Carrasco Gomez, J. (CoI), Da Via, C. (CoI), Furber, S. (CoI), Luján, M. (CoI), Watson, S. (CoI), Watts, S. (CoI) & Weightman, A. (CoI)
2/10/17 → 31/03/22
Project: Research
Research output
- 1 Conference contribution
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Microwave Sensing for Avoidance of High-Risk Ground Conditions for Mobile Robots
Blanche, J., Mitchell, D., West, A., Harper, S., Groves, K., Lennox, B., Watson, S. & Flynn, D., 27 Jul 2023, (E-pub ahead of print) IEEE International Conference on Omni-Layer Intelligent Systems (COINS) 2023. IEEEResearch output: Chapter in Book/Conference proceeding › Conference contribution › peer-review
Open AccessFile