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The nuclear energy sector can benefit from mobile robots for remote inspection and handling, reducing human exposure to radiation. Advances in cyber–physical systems have improved robotic platforms in this sector through digital twin (DT) technology. DTs enhance situational awareness for robot operators, crucial for safety in the nuclear energy sector, and their value is anticipated to increase with the growing complexity of cyber–physical systems. The primary motivation of this work is to rapidly develop and evaluate a robot fleet interface that accounts for these benefits in the context of nuclear environments. Here, we introduce a multimodal immersive DT platform for cyber–physical robot fleets based on the ROS‐Unity 3D framework. The system design enables fleet monitoring and management by integrating building information models, mission parameters, robot sensor data, and multimodal user interaction through traditional and virtual reality interfaces. A modified heuristic evaluation approach, which accounts for the positive and negative aspects of the interface, was introduced to accelerate the iterative design process of our DT platform. Robot operators from leading nuclear research institutions (Sellafield Ltd. and the Japan Atomic Energy Agency) performed a simulated robot inspection mission while providing valuable insights into the design elements of the cyber–physical system. The three usability themes that emerged and inspired our design recommendations for future developers include increasing the interface's flexibility, considering each robot's individuality, and adapting the platform to expand sensor visualization capabilities. [ABSTRACT FROM AUTHOR]

Physically inspired models of the stochastic nature of the human-robot-environment interaction are generally difficult to derive from first principles, thus alternative data-driven approaches are an attractive option. In this article, Gaussian process regression is used to model a safe stop maneuver for a teleoperated robot. In the proposed approach, a limited number of discrete experimental training data points are acquired to fit (or learn) a Gaussian process model, which is then used to predict the evolution of the process over a desired continuous range (or domain). A confidence measure for those predictions is used as a tuning parameter in a shared control algorithm, and it is demonstrated that it can be used to assist a human operator by providing (low-level) obstacle avoidance when they utilize the robot to carry out safety-critical tasks that involve remote navigation using the robot. The algorithm is personalized in the sense that it can be tuned to match the specific driving style of the person that is teleoperating the robot over a specific terrain. Experimental results demonstrate that with the proposed shared controller enabled, the human operator is able to more easily maneuver the robot in environments with (potentially dangerous) static obstacles, thus keeping the robot safe and preserving the original state of the surroundings. The future evolution of this work will be to apply this shared controller to mobile robots that are being deployed to inspect hazardous nuclear environments, ensuring that they operate with increased safety. [ABSTRACT FROM AUTHOR]

This paper presents the Vega robot, which is a small, low cost, potentially disposable ground robot designed for nuclear decommissioning. Vega has been developed specifically to support characterization and inspection operations, such as 2D and 3D mapping, radiation scans and sample retrieval. The design and construction methodology that was followed to develop the robot is described and its capabilities detailed. Vega was designed to provide flexibility, both in software and hardware, is controlled via tele‐operation, although it can be extended to semi and full autonomy, and can be used in either tethered or untethered configurations. A version of the tethered robot was designed for extreme radiation tolerance, utilizing relay electronics and removing active electronic systems. Vega can be outfitted with a multitude of sensors and actuators, including gamma spectrometers, alpha/beta radiation sensors, LiDARs and robotic arms. To demonstrate its flexibility, a 5 degree‐of‐freedom manipulator has been successfully integrated onto Vega, facilitating deployments where handling is required. To assess the tolerance of Vega to the levels of ionizing radiation that may be found in decommissioning environments, its individual components were irradiated, allowing estimates to be made of the length of time Vega would be able to continue to operate in nuclear environments. Vega has been successfully deployed in an active environment at the Dounreay nuclear site in the UK, deployed in nonactive environments at the Atomic Weapons Establishment, and demonstrated to many other organizations in the UK nuclear industry including Sellafield Ltd, with the goal of moving to active deployments in the future. [ABSTRACT FROM AUTHOR]

Coordination of robot swarms has received significant research interest over the last decade due to its wide real-world applications including precision agriculture, target surveillance, planetary exploration, etc. Many of these practical activities can be formulated as a formation tracking problem. This brief aims to design a robust control strategy for networked robot swarms subjected to nonlinear dynamics and unknown disturbances. Firstly, a robust adaptive formation coordination protocol is proposed for robot swarms, which utilizes only local information for tracking a dynamic target with uncertain maneuvers. A rigorous theoretical proof utilizing the Lyapunov stability approach is then provided to guarantee the control performance. Towards the end, real-time hardware experiments with wheeled mobile robots are conducted to validate the robustness and feasibility of the proposed formation coordination approach. [ABSTRACT FROM AUTHOR]

Flocking is a social animals' common behaviour observed in nature. It has a great potential for real-world applications such as exploration in agri-robotics using low-cost robotic solutions. In this paper, an extended model of a self-organised flocking mechanism using heterogeneous swarm system is proposed. The proposed model for swarm robotic systems is a combination of a collective motion mechanism with obstacle avoidance functions, which ensures a collision-free flocking trajectory for the followers. An optimal control model for the leader is also developed to steer the swarm to a desired goal location. Compared to the conventional methods, by using the proposed model, the swarm network has less requirement for power and storage. The feasibility of the proposed self-organised flocking algorithm is validated by realistic robotic simulation software. [ABSTRACT FROM AUTHOR]

This brief proposes a bearing-only collision-free formation coordination strategy for networked heterogeneous robots, where each robot only measures the relative bearings of its neighbors to achieve cooperation. Different from many existing studies that can only guarantee global asymptotic stability (i.e., the formation can only be formed over an infinite settling period), a gradient-descent control protocol is designed to make the robots achieve a target formation within a given finite time. The stability of the multi-robot system is guaranteed via Lyapunov theory, and the convergence time can be defined by users. Moreover, we also present sufficient conditions for collision avoidance. Finally, a simulation case study is provided to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Time delays exist in network-connected systems. Especially for vision-based multirobot systems, time delays are diverse and complicated due to the communication network, camera latency, image processing, etc. At the same time, many tasks, such as searching and rescue, have timing requirement. This paper focuses on fixed-time formation control of multirobot systems subject to delay constraints. First, predictor-based state transformation is employed for each robot to deal with the input delay, and the uncertain terms remained in the transformed systems are carefully considered. Then, a couple of nonlinear fixed-time formation protocols are proposed for the multirobot systems with respectively undirected and directed topology, and the corresponding settling time is derived by using the Lyapunov functions. In particular, the upper-bound estimation of the formation settling time is explicitly given irrelevant to the initial conditions. Finally, the protocols are validated through a numerical simulation example and then implemented on an E-puck robots platform. Both simulation and experimental results demonstrate the effectiveness of the proposed formation protocols. [ABSTRACT FROM AUTHOR]

Swarm robotics focuses on decentralised control of large numbers of simple robots with limited capabilities. Decentralised control in a swarm system requires a reliable communication link between the individuals that is able to provide linear and angular distances between the individuals—Range & Bearing. This study presents the development of an open-source, low-cost communication module which can be attached to miniature sized robots; e.g., Mona. In this study, we only focused on bearing estimation to mathematically model the bearings of neighbouring robots through systematic experiments using real robots. In addition, the model parameters were optimised using a genetic algorithm to provide a reliable and precise model that can be applied for all robots in a swarm. For further investigation and improvement of the system, an additional layer of optimisation on the hardware layout was implemented. The results from the optimisation suggested a new arrangement of the sensors with slight angular displacements on the developed board. The precision of bearing was significantly improved by optimising in both software level and re-arrangement of the sensors' positions on the hardware layout. [ABSTRACT FROM AUTHOR]