A review of ground-based robotic systems for the characterization of nuclear environments

An efficient grasping shared control architecture for unpredictable and unspecified tasks

Robot control in complex and unpredictable scenarios presents challenges such as adaptability, robustness, and human-robot interaction. These scenarios often require robots to perform tasks that involve unknown objects in unstructured environments with high levels of uncertainty. Traditional control methods, such as automatic control, may not be suitable due to their limited adaptability and reliance on prior knowledge. Human-in-the-loop method faces issues such as insufficient feedback, increased failure rates due to noise and delays, and lack of operator immersion, preventing the achievement of human-level performance. This study proposed a shared control framework to achieve a trade-off between efficiency and adaptability by combing the advantages of both teleoperation and automatic control method. The proposed approach combines the advantages of both human and automatic control methods to achieve a balance between performance and adaptability. We developed a linear model to compare three control methods and analyzed the impact of position noise and communication delays on performance. The real-world implementation of the shared control system demonstrates its effectiveness in object grasping and manipulation tasks. The results suggest that shared control can significantly improve grasping efficiency while maintaining adaptability in task execution for practical robotics applications.

Path to autonomous soil sampling and analysis by ground-based robots

Good site characterization is essential for the selection of remediation alternatives for impacted soils. The value of site characterization is critically dependent on the quality and quantity of the data collected. Current methods for characterizing impacted soils rely on expensive manual sample collection and off-site analysis. However, recent advances in terrestrial robotics and artificial intelligence offer a potentially revolutionary set of tools and methods that will help to autonomously explore natural environments, select sample locations with the highest value of information, extract samples, and analyze the data in real-time without exposing humans to potentially hazardous conditions. A fundamental challenge to realizing this potential is determining how to design an autonomous system for a given investigation with many, and often conflicting design criteria. This work presents a novel design methodology to navigate these criteria. Specifically, this methodology breaks the system into four components - sensing, sampling, mobility, and autonomy - and connects design variables to the investigation objectives and constraints. These connections are established for each component through a survey of existing technology, discussion of key technical challenges, and highlighting conditions where generality can promote multi-application deployment. An illustrative example of this design process is presented for the development and deployment of a robotic platform characterizing salt-impacted oil & gas reserve pits. After calibration, the relationship between the in situ robot chloride measurements and laboratory-based chloride measurements had a good linear relationship (R2-value = 0.861) and statistical significance (p-value = 0.003).

Principles and methods of liquid metal actuators

As a promising material, liquid metals (LMs) have gained considerable interest in the field of soft robotics due to their ability to move as designed routines or change their shape dramatically under external stimuli. Inspired by the science fiction film Terminator, tremendous efforts have been devoted to liquid robots with high compliance and intelligence. How to manipulate LM droplets is crucial to achieving this goal. Accordingly, this review is dedicated to presenting the principles driving LMs and summarizing the potential methods to develop LM actuators of high maneuverability. Moreover, the recent progress of LM robots based on these methods is overviewed. The challenges and prospects of implementing autonomous robots have been proposed.

A Review of Approaches for Mitigating Effects from Variable Operational Environments on Piezoelectric Transducers for Long-Term Structural Health Monitoring

Extending the service life of ageing infrastructure, transportation structures, and processing and manufacturing plants in an era of limited resources has spurred extensive research and development in structural health monitoring systems and their integration. Even though piezoelectric transducers are not the only sensor technology for SHM, they are widely used for data acquisition from, e.g., wave-based or vibrational non-destructive test methods such as ultrasonic guided waves, acoustic emission, electromechanical impedance, vibration monitoring or modal analysis, but also provide electric power via local energy harvesting for equipment operation. Operational environments include mechanical loads, e.g., stress induced deformations and vibrations, but also stochastic events, such as impact of foreign objects, temperature and humidity changes (e.g., daily and seasonal or process-dependent), and electromagnetic interference. All operator actions, correct or erroneous, as well as unintentional interference by unauthorized people, vandalism, or even cyber-attacks, may affect the performance of the transducers. In nuclear power plants, as well as in aerospace, structures and health monitoring systems are exposed to high-energy electromagnetic or particle radiation or (micro-)meteorite impact. Even if environmental effects are not detrimental for the transducers, they may induce large amounts of non-relevant signals, i.e., coming from sources not related to changes in structural integrity. Selected issues discussed comprise the durability of piezoelectric transducers, and of their coupling and mounting, but also detection and elimination of non-relevant signals and signal de-noising. For long-term service, developing concepts for maintenance and repair, or designing robust or redundant SHM systems, are of importance for the reliable long-term operation of transducers for structural health monitoring.

CARMA II: A ground vehicle for autonomous surveying of alpha, beta and gamma radiation

Surveying active nuclear facilities for spread of alpha and beta contamination is currently performed by human operators. However, a skills gap of qualified workers is emerging and is set to worsen in the near future due to under recruitment, retirement and increased demand. This paper presents an autonomous ground vehicle that can survey nuclear facilities for alpha, beta and gamma radiation and generate radiation heatmaps. New methods for preventing the robot from spreading radioactive contamination using a state-machine and radiation costmaps are introduced. This is the first robot that can detect alpha and beta contamination and autonomously re-plan around the contamination without the wheels passing over the contaminated area. Radiation avoidance functionality is proven experimentally to reduce alpha and beta contamination spread as well as gamma radiation dose to the robot. The robot’s survey area is defined using a custom designed, graphically controlled area coverage planner. It was concluded that the robot is highly suited to certain monotonous room scale radiation surveying tasks and therefore provides the opportunity for financial savings, to mitigate a future skills gap, and provision of radiation surveys that are more granular, accurate and repeatable than those currently performed by human operators.

Autonomous search of an airborne release in urban environments using informed tree planning

The use of autonomous vehicles for source localisation is a key enabling tool for disaster response teams to safely and efficiently deal with chemical emergencies. Whilst much work has been performed on source localisation using autonomous systems, most previous works have assumed an open environment or employed simplistic obstacle avoidance, separate from the estimation procedure. In this paper, we explore the coupling of the path planning task for both source term estimation and obstacle avoidance in an adaptive framework. The proposed system intelligently produces potential gas sampling locations that will reliably inform the estimation engine by not sampling in the wake of buildings as frequently. Then a tree search is performed to generate paths toward the estimated source location that traverse around any obstacles and still allow for exploration of potentially superior sampling locations.The proposed informed tree planning algorithm is then tested against the standard Entrotaxis and Entrotaxis-Jump techniques in a series of high fidelity simulations. The proposed system is found to reduce source estimation error far more efficiently than its competitors in a feature rich environment, whilst also exhibiting vastly more consistent and robust results.

Design and Study of a Stair Climbing Robots with Two Wheels and a “4R+2P” Pattern

Aimed at the current major problems of “slipping, misstep and misplace” in the robot stair climbing process and at reaching the goals of being “flexible, adaptive and stable” in multiple scenarios, a two-wheeled robot with a “4R+2P” pattern that can independently climb different structures of stairs is proposed, and a gait pattern for stair climbing through a four-step cycle of “approaching, lifting, putting and retraction” based on this pattern is proposed. Relevant kinematic and dynamic models are established to study the constraint relation. In the experiment, the robot goes up and down different stairs. The simulation and experimental results showed that the two-wheeled robot with a “4R+2P” configuration fundamentally realized up–down stair climbing, adaptive steering and multiscene functions.

A coverage path planning approach for autonomous radiation mapping with a mobile robot

In nuclear and radiation-related industries, it is crucial to ensure that the radiation dose exposure to the radiation worker is maintained below the permissible dose limit. A radiation map is a useful tool for visualizing the radiation distribution across the work area and for coordinating activities involving the hotspots (high radiation areas). The goal of this work was to design and implement a coverage path planning approach for autonomous radiation mapping carried out by a mobile robot. Given a 2D occupancy map, a method to generate uniformly distributed sampling points was proposed. The geometry of the region of interest, the radiation detector module, and the radiation measurement parameters were considered in formulating the sampling positions. Next, the coverage path planning planner integrates the nearest neighbor and depth-first search algorithms to create a continuous path that enables the robot to visit all the sampling points. The K-means clustering algorithm is added for systematic coverage of a large number of sampling points. The clustering provides options to partition the region of interest into smaller spaces, where the robot would perform the mapping cluster by cluster. Finally, the method of building the radiation map from the acquired data was also presented. The approach was implemented in ROS using a commercial mobile robot equipped with a Geiger–Muller detector. The performance and reliability of the proposed approach were evaluated with a series of simulations and real-world experiments. The results showed that the robot is able to perform autonomous radiation mapping at various target areas. The accuracy of the generated radiation map and the hotspots classifications were also compared and evaluated with conventional manual measurements. Overall, the theoretical frameworks and experiments have provided convincing results in the automation of hazardous work and subsequently toward improving the occupational safety of radiation workers.

Real-Time Avoidance of Ionising Radiation Using Layered Costmaps for Mobile Robots

Humans in hazardous environments take actions to reduce unnecessary risk, including limiting exposure to radioactive materials where ionising radiation can be a threat to human health. Robots can adopt the same approach of risk avoidance to minimise exposure to radiation, therefore limiting damage to electronics and materials. Reducing a robot’s exposure to radiation results in longer operational lifetime and better return on investment for nuclear sector stakeholders. This work achieves radiation avoidance through the use of layered costmaps, to inform path planning algorithms of this additional risk. Interpolation of radiation observations into the configuration space of the robot is accomplished using an inverse distance weighting approach. This technique was successfully demonstrated using an unmanned ground vehicle running the Robot Operating System equipped with compatible gamma radiation sensors, both in simulation and in real-world mock inspection missions, where the vehicle was exposed to radioactive materials in Lancaster University’s Neutron Laboratory. The addition of radiation avoidance functionality was shown to reduce total accumulated dose to background levels in real-world deployment and up to a factor of 10 in simulation.

Kinematic and dynamic control model of wheeled mobile robot under internet of things and neural network

This study aims to solve the issues of nonlinearity, non-integrity constraints, under-actuated systems in mobile robots. The wheeled robot is selected as the research object, and a kinematic and dynamic control model based on Internet of Things (IoT) and neural network is proposed. With the help of IoT sensors, the proposed model can realize effective control of the mobile robot under the premise of ensuring safety using the model tracking scheme and the radial basis function adaptive control algorithm. The results show that the robot can be controlled effectively to break the speed and acceleration constraints using the strategy based on the model predictive control, thus realizing smooth movement under the premise of safety. The self-adapting algorithm based on the IoT and neural network shows notable advantages in parameter uncertainty and roller skidding well. The proposed model algorithm shows a fast convergence rate of about 2 s, which has effectively improved performances in trajectory tracking and robustness of the wheeled mobile robot, and can solve the difficulties of wheeled mobile robots in practical applications, showing reliable reference value for algorithm research in this field.

A Low-Cost and Semi-Autonomous Robotic Scanning System for Characterising Radiological Waste

A novel, semi-autonomous radiological scanning system for inspecting irregularly shaped and radiologically uncharacterised objects in various orientations is presented. The system utilises relatively low cost, commercial-off-the-shelf (COTS) electronic components, and is intended for use within relatively low to medium radioactive dose environments. To illustrate the generic concepts, the combination of a low-cost COTS vision system, a six DoF manipulator and a gamma radiation spectrometer are investigated. Three modes of vision have been developed, allowing a remote operator to choose the most appropriate algorithm for the task. The robot arm subsequently scans autonomously across the selected object, determines the scan positions and enables the generation of radiological spectra using the gamma spectrometer. These data inform the operator of any likely radioisotopes present, where in the object they are located and thus whether the object should be treated as LLW, ILW or HLW.

Assessing the Role of Gaze Tracking in Optimizing Humans-In-The-Loop Telerobotic Operation Using Multimodal Feedback

A key challenge in achieving effective robot teleoperation is minimizing teleoperators’ cognitive workload and fatigue. We set out to investigate the extent to which gaze tracking data can reveal how teleoperators interact with a system. In this study, we present an analysis of gaze tracking, captured as participants completed a multi-stage task: grasping and emptying the contents of a jar into a container. The task was repeated with different combinations of visual, haptic, and verbal feedback. Our aim was to determine if teleoperation workload can be inferred by combining the gaze duration, fixation count, task completion time, and complexity of robot motion (measured as the sum of robot joint steps) at different stages of the task. Visual information of the robot workspace was captured using four cameras, positioned to capture the robot workspace from different angles. These camera views (aerial, right, eye-level, and left) were displayed through four quadrants (top-left, top-right, bottom-left, and bottom-right quadrants) of participants’ video feedback computer screen, respectively. We found that the gaze duration and the fixation count were highly dependent on the stage of the task and the feedback scenario utilized. The results revealed that combining feedback modalities reduced the cognitive workload (inferred by investigating the correlation between gaze duration, fixation count, task completion time, success or failure of task completion, and robot gripper trajectories), particularly in the task stages that require more precision. There was a significant positive correlation between gaze duration and complexity of robot joint movements. Participants’ gaze outside the areas of interest (distractions) was not influenced by feedback scenarios. A learning effect was observed in the use of the controller for all participants as they repeated the task with different feedback combination scenarios. To design a system for teleoperation, applicable in healthcare, we found that the analysis of teleoperators’ gaze can help understand how teleoperators interact with the system, hence making it possible to develop the system from the teleoperators’ stand point.

The Characterization of Silicone-Tungsten-Based Composites as Flexible Gamma-Ray Shields

Robots are very essential for modern nuclear power plants to monitor equipment conditions and eliminate accidents, allowing one to reduce the radiations on personnel. As a novel robot, a soft robot with the advantages of more degrees of freedom and abilities of continuously bending and twisting has been proposed and developed for applications in nuclear power industry. Considering the radiation and high-temperature environment, the overall performance improvement of the flexible materials used in the soft nuclear robot, such as the tensile property and gamma-ray shielding property, is an important issue, which should be paid attention. Here, a flexible gamma-ray shielding material silicone-W-based composites were initially doped with nano titanium oxide and prepared, with the composition of 20 silicone-(80-x) W-(x) TiO2, where x varied from 0.1 to 2.0 wt.%. Structural investigations on SEM and EDS were performed to confirm the structure of the prepared composites and prove that all the chemicals were included in the compositions. Moreover, the tensile property of the composites at 25, 100, and 150 °C were investigated to study the effect of working temperature on the flexibility of the compositions. The attenuation characteristics including the linear attenuation coefficients and mass attenuation coefficients of the prepared silicone-W or silicone-W-TiO2-based composites with respect to gamma ray were investigated. The stability of the silicone-tungsten-TiO2-based composite at high temperature was studied for the first time. In addition, the influence of nano TiO2 additive on the property's variation of silicone-W-based composites was initially studied. The comparison of the properties such as the tensile elongation, thermal stability, and gamma-ray shielding of the synthesized silicone-W and silicone-W-TiO2 composites showed that the addition of nano TiO2 powders could be useful to develop novel gamma-ray-shielding materials for radiation protection of soft robots or other applications for which soft gamma-ray-shielding materials are needed.

An Intermetallic NiTi-Based Shape Memory Coil Spring for Actuator Technologies

Amongst various intermetallic shape memory alloys (SMAs), nickel–titanium-based SMAs (NiTi) are known for their unique elastocaloric property. This widely used shape remembering material demonstrates excellent mechanical and electrical properties with superior corrosion resistance and super-long fatigue life. The straight-drawn wire form of NiTi has a maximum restorable strain limit of ~4%. However, a maximum linear strain of ~20% can be attained in its coil spring structure. Various material/mechanical engineers have widely exploited this superior mechanic characteristic and stress-triggered heating/cooling efficiency of NiTi to design smart engineering structures, especially in actuator technologies. This short technical note reflects the characteristics of the NiTi coil spring structure with its phase transformations and thermal transformation properties. The micro-actuators based on NiTi have been found to be possible, suggesting uses from biomedical to advanced high-tech applications. In recent years, the technical advancements in modular robotic systems involving NiTi-based SMAs have gained speculative commercial interest.

Use of Gaussian process regression for radiation mapping of a nuclear reactor with a mobile robot

Collection and interpolation of radiation observations is of vital importance to support routine operations in the nuclear sector globally, as well as for completing surveys during crisis response. To reduce exposure to ionizing radiation that human workers can be subjected to during such surveys, there is a strong desire to utilise robotic systems. Previous approaches to interpolate measurements taken from nuclear facilities to reconstruct radiological maps of an environment cannot be applied accurately to data collected from a robotic survey as they are unable to cope well with irregularly spaced, noisy, low count data. In this work, a novel approach to interpolating radiation measurements collected from a robot is proposed that overcomes the problems associated with sparse and noisy measurements. The proposed method integrates an appropriate kernel, benchmarked against the radiation transport code MCNP6, into the Gaussian Process Regression technique. The suitability of the proposed technique is demonstrated through its application to data collected from a bespoke robotic system used to conduct a survey of the Joz̆ef Stefan Institute TRIGA Mark II nuclear reactor during steady state operation, where it is shown to successfully reconstruct gamma dosimetry estimates in the reactor hall and aid in identifying sources of ionizing radiation.

Simulating Ionising Radiation in Gazebo for Robotic Nuclear Inspection Challenges

The utilisation of robots in hazardous nuclear environments has potential to reduce risk to humans. However, historical use has been largely limited to specific missions rather than broader industry-wide adoption. Testing and verification of robotics in realistic scenarios is key to gaining stakeholder confidence but hindered by limited access to facilities that contain radioactive materials. Simulations offer an alternative to testing with actual radioactive sources, provided they can readily describe the behaviour of robotic systems and ionising radiation within the same environment. This work presents a quick and easy way to generate simulated but realistic deployment scenarios and environments which include ionising radiation, developed to work within the popular robot operating system compatible Gazebo physics simulator. Generated environments can be evolved over time, randomly or user-defined, to simulate the effects of degradation, corrosion or to alter features of certain objects. Interaction of gamma radiation sources within the environment, as well as the response of simulated detectors attached to mobile robots, is verified against the MCNP6 Monte Carlo radiation transport code. The benefits these tools provide are highlighted by inclusion of three real-world nuclear sector environments, providing the robotics community with opportunities to assess the capabilities of robotic systems and autonomous functionalities.

Robotic arm material characterisation using LIBS and Raman in a nuclear hot cell decommissioning environment

Material characterisation in nuclear environments is an essential part of decommissioning processes. This paper explores the feasibility of deploying commercial off the shelf (COTS) laser induced breakdown spectroscopy (LIBS) and Raman spectroscopy, for use in a decommissioning hot cell environment, to inform waste operation decision making. To operate these techniques, adapters and probes were designed and constructed, for each instrument, to form tools that a robotic arm could pick up and operate remotely from an isolated control room. The developed instrumentation successfully returned live measurement data to a control room for saving and further analysis (e.g. material classification/identification). Successful testing of the solutions was performed for contact LIBS, contact Raman and stand-off Raman on a PaR M3000 robotic arm, in a simulated hot cell environment and the limitations identified. Data obtained by the techniques are analysed, classified and presented in a 3D virtual environment. The spectral data collected by a basic COTS LIBS showed potential for use in contamination identification (beryllium is used as example). Potential for COTS, LIBS and Raman in decommissioning is established and improvements to the hardware, the measurement processes and how the data is stored and used, are identified.

Progress in robotics for combating infectious diseases

The world was unprepared for the COVID-19 pandemic, and recovery is likely to be a long process. Robots have long been heralded to take on dangerous, dull, and dirty jobs, often in environments that are unsuitable for humans. Could robots be used to fight future pandemics? We review the fundamental requirements for robotics for infectious disease management and outline how robotic technologies can be used in different scenarios, including disease prevention and monitoring, clinical care, laboratory automation, logistics, and maintenance of socioeconomic activities. We also address some of the open challenges for developing advanced robots that are application oriented, reliable, safe, and rapidly deployable when needed. Last, we look at the ethical use of robots and call for globally sustained efforts in order for robots to be ready for future outbreaks.

An assessment of contamination pickup on ground robotic vehicles for nuclear surveying application

Ground robotic vehicles are often deployed to inspect areas where radioactive floor contamination is a prominent risk. However, the accuracy of detection could be adversely affected by enhanced radiation signal through self-contamination of the robot occurring over the course of the inspection. In this work, it was hypothesised that a six-legged robot could offer advantages over the more conventional ground robotic devices such as wheeled and tracked rovers. To investigate this, experimental contamination testing and computational Monte Carlo simulation techniques (GEANT4) were employed to understand how radioactive contamination pick-up on three different robotic vehicles would affect their detection accuracy. Two robotic vehicles were selected for comparison with the hexapod robot based on their type of locomotion; a wheeled rover and a tracked rover. With the aid of a non-toxic fluorescent tracer dust, the contamination received by the all three vehicles when traversing a contaminated area was initially compared through physical inspection using high definition cameras. The parametric results from these tests where used in the computational study carried out in GEANT4. A cadmium zinc telluride detector was simulated at heights ranging from 10 to 50 cm above each contaminated vehicle, as if it were mounted on a plinth. Assuming a uniform activity of 60 Bq cm^-2on all contaminated surfaces, the results suggested that due to the hexapod's small ground-contacting surface area and geometry, radiation detection rates using an uncollimated detector are likely to be overestimated by between only 0.07%-0.12%, compared with 3.95%-8.43% and 1.75%-14.53% for the wheeled and tracked robot alternatives, respectively.

Robotic Exploration of an Unknown Nuclear Environment Using Radiation Informed Autonomous Navigation

This paper describes a novel autonomous ground vehicle that is designed for exploring unknown environments which contain sources of ionising radiation, such as might be found in a nuclear disaster site or a legacy nuclear facility. While exploring the environment, it is important that the robot avoids radiation hot spots to minimise breakdowns. Broken down robots present a real problem: they not only cause the mission to fail but they can block access routes for future missions. Until now, such robots have had no autonomous gamma radiation avoidance capabilities. New software algorithms are presented that allow radiation measurements to be converted into a format in which they can be integrated into the robot’s navigation system so that it can actively avoid receiving a high radiation dose during a mission. An unmanned ground vehicle was fitted with a gamma radiation detector and an autonomous navigation package that included the new radiation avoidance software. The full system was evaluated experimentally in a complex semi-structured environment that contained two radiation sources. In the experiment, the robot successfully identified both sources and avoided areas that were found to have high levels of radiation while navigating between user defined waypoints. This advancement in the state-of-the-art has the potential to deliver real benefit to the nuclear industry, in terms of both increased chance of mission success and reduction of the reliance on human operatives to perform tasks in dangerous radiation environments.

Implementation and Evaluation of a Semi-Autonomous Hydraulic Dual Manipulator for Cutting Pipework in Radiologically Active Environments

We describe the implementation of a bespoke two arm hydraulically actuated robotic platform which is used to semi-autonomously cut approximately 50 mm diameter pipes of three different materials: cardboard, ABS plastic and aluminium. The system is designed to be utilised within radiologically active environments where human access is limited due to dose limits and thus remote operation is greatly beneficial. The remotely located operator selects the object from an image via a bespoke algorithm featuring a COTS 3D vision system, along with the desired positions for gripping with one manipulator, and cutting with the other. A pseudo-Jacobian inverse kinematic technique and a programmable automation controller are used to achieve the appropriate joint positions within the dual arm robotic platform. In this article, we present the latest developments to the system and the lessons learnt from the new cutting experiments with a reciprocating saw. A comparison to tele-operated control and manual cutting is also made, with this technique shown to be slower than manual cutting, but faster than pure tele-operational control, where the requirements for highly trained users and operator fatigue are further deleterious factors.

State-of-the-Art Mobile Radiation Detection Systems for Different Scenarios

In the last decade, the development of more compact and lightweight radiation detection systems led to their application in handheld and small unmanned systems, particularly air-based platforms. Examples of improvements are: the use of silicon photomultiplier-based scintillators, new scintillating crystals, compact dual-mode detectors (gamma/neutron), data fusion, mobile sensor networks, cooperative detection and search. Gamma cameras and dual-particle cameras are increasingly being used for source location. This study reviews and discusses the research advancements in the field of gamma-ray and neutron measurements using mobile radiation detection systems since the Fukushima nuclear accident. Four scenarios are considered: radiological and nuclear accidents and emergencies; illicit traffic of special nuclear materials and radioactive materials; nuclear, accelerator, targets, and irradiation facilities; and naturally occurring radioactive materials monitoring-related activities. The work presented in this paper aims to: compile and review information on the radiation detection systems, contextual sensors and platforms used for each scenario; assess their advantages and limitations, looking prospectively to new research and challenges in the field; and support the decision making of national radioprotection agencies and response teams in respect to adequate detection system for each scenario. For that, an extensive literature review was conducted.

Radiation Tolerance Testing Methodology of Robotic Manipulator Prior to Nuclear Waste Handling

Dramatic cost savings, safety improvements and accelerated nuclear decommissioning are all possible through the application of robotic solutions. Remotely-controlled systems with modern sensing capabilities, actuators and cutting tools have the potential for use in extremely hazardous environments, but operation in facilities used for handling radioactive material presents complex challenges for electronic components. We present a methodology and results obtained from testing in a radiation cell in which we demonstrate the operation of a robotic arm controlled using modern electronics exposed at 10 Gy/h to simulate radioactive conditions in the most hazardous nuclear waste handling facilities.

Radiation Mapping and Laser Profiling Using a Robotic Manipulator

The use of a robotic arm manipulator as a platform for coincident radiation mapping and laser profiling of radioactive sources on a flat surface is investigated in this work. A combined scanning head, integrating a micro-gamma spectrometer and Time of Flight (ToF) sensor were moved in a raster scan pattern across the surface, autonomously undertaken by the robot arm over a 600 × 260 mm survey area. A series of radioactive sources of different emission intensities were scanned in different configurations to test the accuracy and sensitivity of the system. We demonstrate that in each test configuration the system was able to generate a centimeter accurate 3D model complete with an overlaid radiation map detailing the emitted radiation intensity and the corrected surface dose rate.

Robotic Development for the Nuclear Environment: Challenges and Strategy

Improvements in robotics and artificial intelligence have enabled robotics to be developed for use in a nuclear environment. However, the harsh environment and dangerous nature of the tasks pose several challenges in deploying robots. There may be some unique requirements for a nuclear application that a commercial system does not meet, such as radiation effects, the needs remote maintenance and deployment constraints. This paper reviews the main challenges that robots need to face to be deployed in a nuclear environment, examines the development and assessment processes required in the nuclear industry, and highlights the assistance that is available for developers. Due to comparable environments and operating restrictions, the development process employed by the nuclear industry has a similar structure as that employed by NASA and the ESA for space exploration. The nuclear industry has introduced a number of development support programs, such as Innovate and Game Changers, to fund and mentor developers through the initial design stages to proving viability in a representative independently assessed test environment. Robust and reliable technologies, which may also have application beyond the original nuclear application, are being successfully developed and tested, enabling robotics in making nuclear operations safer and more efficient. Additional development sources are given in the text.

Allocation of Radiation Shielding Boards to Protect the Urban Search and Rescue Robots from Malfunctioning in the Radioactive Environments Arising from Decommissioning of the Nuclear Facility

A group of Urban Search and Rescue (USAR) Unmanned Ground Vehicles (UGVs) works in the city’s dangerous places that are caused by natural disasters or the decommissioning of nuclear facilities such as the nuclear power plant. Consider the multi sensor platform that the USAR UGV is equipped with, protecting the sensors from the danger that dwells in the working environments is highly related to the success of the USAR mission. The radioactive working environments due to the diffusion of the radioactive materials during the decommissioning of the nuclear facilities are proposed in this work. Radiation shielding boards are used to protect the sensors by installing them on the UGV. Generally, the more shielding boards installed on the UGV, the lower the probability of the sensor malfunctioning. With a large number of UGVs that are used in missions, a large number of shielding boards are needed. Considering the cost of the boards, a conflict between the finite budget and the best protection for the UGV swarm occurs. Due to differences in environments and working times, an asymmetric allocation of shielding boards might protect the UGV swarm better than that by allocating evenly. To minimize the absorption radiation doses, two methods including competitive equilibrium analysis and integer linear programming are proposed. The performances that result from the allocation of the shielding boards by two methods with different budgets are studied.

Modelling of Autonomous Search and Rescue Missions by Interval-Valued Neutrosophic WASPAS Framework

The application of autonomous robots in search and rescue missions represents a complex task which requires a robot to make robust decisions in unknown and dangerous environments. However, imprecise robot movements and small measurement errors obtained by robot sensors can have an impact on the autonomous environment exploration quality, and therefore, should be addressed while designing search and rescue (SAR) robots. In this paper, a novel frontier evaluation strategy is proposed, that address technical, economic, social, and environmental factors of the sustainable environment exploration process, and a new extension of the weighted aggregated sum product assessment (WASPAS) method, modelled under interval-valued neutrosophic sets (IVNS), is introduced for autonomous mobile robots. The general-purpose Pioneer 3-AT robot platform is applied in simulated search and rescue missions, and the conducted experimental assessment shows the proposed method efficiency in commercial and public-type building exploration. By addressing the estimated measurement errors in the initial data obtained by the robot sensors, the proposed decision-making framework provides additional reliability for comparing and ranking candidate frontiers. The interval-valued multi-criteria decision-making method combined with the proposed frontier evaluation strategy enables the robot to exhaustively explore and map smaller SAR mission environments as well as ensure robot safety and efficient energy consumption in relatively larger public-type building environments.

3D Exploration and Navigation with Optimal-RRT Planners for Ground Robots in Indoor Incidents

Navigation and exploration in 3D environments is still a challenging task for autonomous robots that move on the ground. Robots for Search and Rescue missions must deal with unstructured and very complex scenarios. This paper presents a path planning system for navigation and exploration of ground robots in such situations. We use (unordered) point clouds as the main sensory input without building any explicit representation of the environment from them. These 3D points are employed as space samples by an Optimal-RRTplanner (RRT * ) to compute safe and efficient paths. The use of an objective function for path construction and the natural exploratory behaviour of the RRT * planner make it appropriate for the tasks. The approach is evaluated in different simulations showing the viability of autonomous navigation and exploration in complex 3D scenarios.

Reliable Activation of an EPM-Based Clinging Device for Aerial Inspection Robots

This study aims to develop a clinging device for structural inspection robots, which are expected to be used to reduce the cost of inspection of aging civil infrastructure and industrial structures. In a previous study, an electro-permanent magnet (EPM)-based clinging device that could electrically turn on and off the magnetic adhesive force against steel structures was proposed. In this study, a more versatile design of the clinging device was firstly presented, and a considerable difficulty regarding the activation process of the EPM which might impair the reliability of the clinging device was stated based on mathematical modeling and experiments. The concept of a two-step activation process was then presented to overcome the stated difficulty, and its implementation using a limit switch-based contact sensor was successfully demonstrated through collision tests. Furthermore, sensorless realization of contact detection by measuring the induced voltage across the coil of the EPM was proposed, and its feasibility was validated.

Detection of Simulated Fukushima Daichii Fuel Debris Using a Remotely Operated Vehicle at the Naraha Test Facility

The use of robotics in harsh environments, such as nuclear decommissioning, has increased in recent years. Environments such as the Fukushima Daiichi accident site from 2011 and the Sellafield legacy ponds highlight the need for robotic systems capable of deployment in hazardous environments unsafe for human workers. To characterise these environments, it is important to develop robust and accurate localization systems that can be combined with mapping techniques to create 3D reconstructions of the unknown environment. This paper describes the development and experimental verification of a localization system for an underwater robot, which enabled the collection of sonar data to create 3D images of submerged simulated fuel debris. The system was demonstrated at the Naraha test facility, Fukushima prefecture, Japan. Using a camera with a bird’s-eye view of the simulated primary containment vessel, the 3D position and attitude of the robot was obtained using coloured LED markers (active markers) on the robot, landmarks on the test-rig (passive markers), and a depth sensor on the robot. The successful reconstruction of a 3D image has been created through use of a robot operating system (ROS) node in real-time.

Compact Viscometer Prototype for Remote In Situ Analysis of Sludge

On the Sellafield site there are several legacy storage tanks and silos containing sludge of uncertain properties. While there are efforts to determine the chemical and radiological properties of the sludge, to clean out and decommission these vessels, the physical properties need to be ascertained as well. Shear behaviour, density and temperature are the key parameters to be understood before decommissioning activities commence. However, limited access, the congested nature of the tanks and presence of radioactive, hazardous substances severely limit sampling and usage of sophisticated characterisation devices within these tanks and therefore, these properties remain uncertain. This paper describes the development of a cheap, compact, and robust device to analyse the rheological properties of sludge, without the need to extract materials from the site in order to be analysed. Analysis of a sludge test material has been performed to create a suitable benchmark material for the rheological measurements with the prototype. Development of the device is being undertaken with commercial off the shelf (COTS) components and modern rapid prototyping techniques. Using these techniques, an initial prototype for measuring shear parameters of sludge has been developed, using a micro-controller for remote control and data gathering. The device is also compact enough to fit through a 75 mm opening, maximising deployment capabilities.

Vision-Based Assisted Tele-Operation of a Dual-Arm Hydraulically Actuated Robot for Pipe Cutting and Grasping in Nuclear Environments

This article investigates visual servoing for a hydraulically actuated dual-arm robot, in which the user selects the object of interest from an on-screen image, whilst the computer control system implements via feedback control the required position and orientation of the manipulators. To improve on the current joystick direct tele-operation commonly used as standard in the nuclear industry, which is slow and requires extensive operator training, the proposed assisted tele-operation makes use of a single camera mounted on the robot. Focusing on pipe cutting as an example, the new system ensures that one manipulator automatically grasps the user-selected pipe, and appropriately positions the second for a cutting operation. Initial laboratory testing (using a plastic pipe) shows the efficacy of the approach for positioning the manipulators, and suggests that for both experienced and inexperienced users, the task is completed significantly faster than via tele-operation.