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 that are sealed volumes with controlled access for performing handling. While gloveboxes allow operators to perform complex handling tasks, they put operators at considerable risk from breaking the confinement and, historically, serious examples including punctured gloves leading to lifetime doses have occurred. To date, robotic systems have had relatively little impact on the industry, even though it is clear that they offer major opportunities for improving productivity and significantly reducing risks to human health. This work presents the challenges of robotic and AI solutions for nuclear gloveboxes, and introduces a step forward for bringing cutting-edge technology to gloveboxes. The problem statement and challenges are highlighted and then an integrated demonstrator is proposed for robotic handling in nuclear gloveboxes for nuclear material handling. The proposed approach spans from tele-manipulation to shared autonomy, computer vision solutions for robotic manipulation to machine learning solutions for condition monitoring.

For robotic systems involved in challenging environments, it is crucial to be able to identify faults as early as possible. In challenging environments, it is not always possible to explore all of the fault space, thus anomalous data can act as a broader surrogate, where an anomaly may represent a fault or a predecessor to a fault. This paper proposes a method for identifying anomalous data from a robot, whilst using minimal nominal data for training. A Monte Carlo ensemble sampled Variational AutoEncoder was utilised to determine nominal and anomalous data through reconstructing live data. This was tested on simulated anomalies of real data, demonstrating that the technique is capable of reliably identifying an anomaly without any previous knowledge of the system. With the proposed system, we obtained an F1-score of $0.85$ through testing.

The design of real time heat load protection functions for the ITER tokamak first wall (FW) plasma-facing components (PFCs) requires the development of simplified, but reliable control-oriented models. The dynamics of interest in this case encompasses slow changes in plasma shape or transient increases in wall power loading. For this purpose, this study presents a new lightweight framework for simulating the FW thermal response during a plasma discharge, validated against higher fidelity codes and developed in a MATLAB/Simulink environment specifically for rapid prototyping and testing of control schemes. This innovative tool allows the ITER FW heat load controller to be designed in the plasma control system simulation platform (PCSSP) following a model-based approach, where a dynamical model of the physical process to control is an integral part of the controller synthesis procedure.

The plasma control system (PCS) for the first nonactive ITER operation phase will require simultaneous active monitoring and control of many continuous and discrete quantities. Considering the unique challenges ITER will face, all the controllers will be integrated and deployed with very little experimental time dedicated to PCS tuning and development. In order to maximize the efficiency of the ITER PCS design, a formal system engineering approach has been adopted. In a simplified way, the design process starts with the definition of the requirements. Functionalities are then designed and developed in order to meet these requirements. As a last step in the design process, it is important to assess that all the designed functionalities meet the associated requirements and that all the requirements are covered. The many different control functions will be designed and implemented in ITER PCS simulation platform (PCSSP) by different designing teams, both internal and external to ITER Organization. Although each team will be responsible for the independent assessment of the modules they deliver, an extra step is, nevertheless, necessary to guarantee that all the modules still continue to work when connected together. Therefore, integrated assessments will be built from independent assessments and will prove the controllers continue to meet the requirements. For this reason, it is necessary to have a unified workflow for the assessments performed by all the different designing teams. In fact, in order to guarantee a smooth integration assessment, it is important that all the assessments follow the same rules, use the same tools, are provided with the correct information, and are performed on the same platform. In this article, we present the proposed assessment workflow for ITER PCS components and some early impressions gathered from assessments of first delivered modules.