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2024
This paper presents a detailed user study aimed at experimentally comparing the experience levels within bilateral teleoperation. The primary objective is to elucidate the key performance metrics that can effectively evaluate the competency level of human operators. Existing methodologies typically focus on the quantitative psychological evaluatio…
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UKAEA-RACE-PR(25)032024
When using deep reinforcement learning (DRL) to perform multi-robot exploration in unknown environments, the training model may produce actions that lead to unpredictable system behaviours due to the complexity and unpredictability of the surroundings. Therefore, ensuring safe exploration with DRL becomes critical. To tackle this issue, we propo…
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UKAEA-RACE-CP(26)022023
When using mobile robots to perform data collection about the surroundings, the performance might be dissatisfying since the environments could be unknown and challenging. This situation will pose challenges for mobile robot navigation and exploration. To tackle this issue, we propose a consensus-based deep reinforcement learning (DRL) algorithm…
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UKAEA-CCFE-PR(23)1852023
Piping systems that transport coolant and breeding fluid are naturally an essential part of the support system of the nuclear fusion power plants. Following a campaign of operations, the reactor is required to be shut down and maintained entirely. Pipes connected to the reactor components are to be cut, re-welded or re-joined, and inspected non-des…
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UKAEA-RACE-CP(23)092023
When transferring a Deep Reinforcement Learning (DRL) model from simulation to the real world, the performance could be unsatisfactory since the simulation cannot imitate the real world well in many circumstances. This results in a long period of fine-tuning in the real world. This paper proposes a self-supervised vision-based DRL method that al…
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UKAEA-RACE-PR(22)062022
The maturation of Virtual Reality software introduces new avenues of nuclear decommissioning research. Digital Mockups are an emerging technology which provide a virtual representation of the environment, objects or processes, supporting the whole lifecycle of product development and operations. This paper provides a survey on currently available …
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UKAEA-RACE-PR(22)042022
The nuclear industry has some of the most extreme environments in the world, with radiation levels and extremely harsh conditions restraining human access to many facilities. One method for enabling minimal human exposure to hazards under these conditions is through the use of gloveboxes which are sealed volumes with controlled access for perfor…
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UKAEA-RACE-PR(23)022021
Maintenance and inspection systems for future fusion power plants (e.g., STEP and DEMO) are expected to require the integration of hundreds of systems from multiple suppliers, with lifetime expectancies of several decades, where requirements evolve over time and obsolescence management is required. There are significant challenges associated wit…
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UKAEA-RACE-CP(23)022021
Robotic systems that enable the operators to remotely manipulate delicate materials with high dexterity and sufficient force feedback will pave the path for improvements of the safe maintenance and decommissioning processes within the nuclear industry. Training the operators, however, for challenging conditions (e.g., low visibility, restricted …
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UKAEA-RACE-CP(21)042021
Just like most industrial or scientific installations, future fusion reactors will require more or less frequent maintenance. The expected environmental conditions, as well as the necessity of carrying out many maintenance tasks in parallel in result in remote robotic maintenance becoming a necessity in order to minimize the maintenance shutdown du…
Showing 11 - 20 of 27 UKAEA Paper Results