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

Abadi, Bahman Nouri Rahmat; West, Andrew; Nancekievill, Matthew; Ballard, Chris; Lennox, Barry; Marjanović, Ognjen; Groves, Keir

doi:10.3389/frobt.2023.1137750

Cited by 5 publications

(4 citation statements)

References 29 publications

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“…The CARMA2 (Figure 1c) is a mobile robot that is based on the Clearpath Jackal platform and is designed to continuously inspect a map of the ground for radioactive contamination from fixed or migrating sources (Bird et al, 2019;Nouri Rahmat Abadi et al, 2023).…”

Section: Heterogeneous Robot Fleetmentioning

confidence: 99%

Multimodal immersive digital twin platform for cyber–physical robot fleets in nuclear environments

Baniqued,

Bremner,

Sandison

et al. 2024

Journal of Field Robotics

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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.

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Section: Heterogeneous Robot Fleetmentioning

confidence: 99%

Multimodal immersive digital twin platform for cyber–physical robot fleets in nuclear environments

Baniqued,

Bremner,

Sandison

et al. 2024

Journal of Field Robotics

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“…Once the mapping process is completed, the second stage involves distributing RPs throughout the mapped area using the RP generation tool [ 53 ]. This tool utilizes a dynamically adjusted marker pattern on a 2D grid map within the GUI, as shown in Figure 7 .…”

Section: Cyber-physical Wireless Indoor Positioning Systemmentioning

confidence: 99%

“…This approach enables the construction of highly adaptable radio maps for new scenarios or changes in environmental conditions or AP locations, thereby overcoming the limitations of scalability and laborious data collection typically associated with fingerprint-based methods. Once the mapping process is completed, the second stage involves distributing RPs throughout the mapped area using the RP generation tool [53]. This tool utilizes a dynamically adjusted marker pattern on a 2D grid map within the GUI, as shown in Figure 7.…”

Section: Interactive and Autonomous Wi-fi Site Surveymentioning

confidence: 99%

Cyber-WISE: A Cyber-Physical Deep Wireless Indoor Positioning System and Digital Twin Approach

Karakusak,

Kivrak,

Watson

et al. 2023

Sensors

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In recent decades, there have been significant research efforts focusing on wireless indoor localization systems, with fingerprinting techniques based on received signal strength leading the way. The majority of the suggested approaches require challenging and laborious Wi-Fi site surveys to construct a radio map, which is then utilized to match radio signatures with particular locations. In this paper, a novel next-generation cyber-physical wireless indoor positioning system is presented that addresses the challenges of fingerprinting techniques associated with data collection. The proposed approach not only facilitates an interactive digital representation that fosters informed decision-making through a digital twin interface but also ensures adaptability to new scenarios, scalability, and suitability for large environments and evolving conditions during the process of constructing the radio map. Additionally, it reduces the labor cost and laborious data collection process while helping to increase the efficiency of fingerprint-based positioning methods through accurate ground-truth data collection. This is also convenient for working in remote environments to improve human safety in locations where human access is limited or hazardous and to address issues related to radio map obsolescence. The feasibility of the cyber-physical system design is successfully verified and evaluated with real-world experiments in which a ground robot is utilized to obtain a radio map autonomously in real-time in a challenging environment through an informed decision process. With the proposed setup, the results demonstrate the success of RSSI-based indoor positioning using deep learning models, including MLP, LSTM Model 1, and LSTM Model 2, achieving an average localization error of ≤2.16 m in individual areas. Specifically, LSTM Model 2 achieves an average localization error as low as 1.55 m and 1.97 m with 83.33% and 81.05% of the errors within 2 m for individual and combined areas, respectively. These outcomes demonstrate that the proposed cyber-physical wireless indoor positioning approach, which is based on the application of dynamic Wi-Fi RSS surveying through human feedback using autonomous mobile robots, effectively leverages the precision of deep learning models, resulting in localization performance comparable to the literature. Furthermore, they highlight its potential for suitability for deployment in real-world scenarios and practical applicability.

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“…The facility was created to remove the challenges associated with working on nuclear sites and provides an intermediate stage for testing RAS in a facility that mirrors obstacles found at Sellafield Ltd. [44]. The SMuRF consisted of Boston Dynamics SPOT with ARM, Agile X Scout 2.0 and mini, Clearpath Jackal (Continuous Autonomous Radiometric Monitoring Assistant (CARMA)) [45], Franka robotic manipulator Arm and DJI Tello Drone. The demonstration of the SMuRF included an analogue environment scenario where UK regulation requires nuclear operators to access and complete characterisation of a site every 3-6 months to assess for radiation levels and asset health monitoring.…”

Section: Introductionmentioning

confidence: 99%

Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments

Mitchell,

Emor Baniqued,

Zahid

et al. 2023

IET Cyber-Syst and Robotics

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Nuclear facilities have a regulatory requirement to measure radiation levels within Post Operational Clean Out (POCO) around nuclear facilities each year, resulting in a trend towards robotic deployments to gain an improved understanding during nuclear decommissioning phases. The UK Nuclear Decommissioning Authority supports the view that human‐in‐the‐loop (HITL) robotic deployments are a solution to improve procedures and reduce risks within radiation characterisation of nuclear sites. The authors present a novel implementation of a Cyber‐Physical System (CPS) deployed in an analogue nuclear environment, comprised of a multi‐robot (MR) team coordinated by a HITL operator through a digital twin interface. The development of the CPS created efficient partnerships across systems including robots, digital systems and human. This was presented as a multi‐staged mission within an inspection scenario for the heterogeneous Symbiotic Multi‐Robot Fleet (SMuRF). Symbiotic interactions were achieved across the SMuRF where robots utilised automated collaborative governance to work together, where a single robot would face challenges in full characterisation of radiation. Key contributions include the demonstration of symbiotic autonomy and query‐based learning of an autonomous mission supporting scalable autonomy and autonomy as a service. The coordination of the CPS was a success and displayed further challenges and improvements related to future MR fleets.

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

Cited by 5 publications

References 29 publications

Multimodal immersive digital twin platform for cyber–physical robot fleets in nuclear environments

Multimodal immersive digital twin platform for cyber–physical robot fleets in nuclear environments

Cyber-WISE: A Cyber-Physical Deep Wireless Indoor Positioning System and Digital Twin Approach

Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments

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