A Framework for Real-Time Autonomous Robotic Sorting and Segregation of Nuclear Waste: Modelling, Identification and Control of DexterTM Robot

Robots are essential for carrying out tasks, for example, in a nuclear industry, where direct human involvement is limited. However, present-day nuclear robots are not versatile due to limited autonomy and higher costs. This research presents a merely teleoperated DexterTM nuclear robot’s transformation into an autonomous manipulator for nuclear sort and segregation tasks. The DexterTM system comprises a arm client manipulator designed to operate in extreme radiation environments and a similar single/dual-arm local manipulator. In this paper, initially, a kinematic model and convex optimization-based dynamic model identification of a single-arm DexterTM manipulator is presented. This model is used for autonomous DexterTM control through Robot Operating System (ROS). A new integration framework incorporating vision, AI-based grasp generation and an intelligent radiological surveying method for enhancing the performance of autonomous DexterTM is presented. The efficacy of the framework is demonstrated on a mock-up nuclear waste test-bed using similar waste materials found in the nuclear industry. The experiments performed show potency, generality and applicability of the proposed framework in overcoming the entry barriers for autonomous systems in regulated domains like the nuclear industry.

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Publication Details

Journal
Machines
Published
2025-03-06
DOI
https://doi.org/10.3390/machines13030214
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

A Framework for Real-Time Autonomous Robotic Sorting and Segregation of Nuclear Waste: Modelling, Identification and Control of DexterTM Robot

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Robotic Path Planning Algorithms
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A Framework for Real-Time Autonomous Robotic Sorting and Segregation of Nuclear Waste: Modelling, Identification and Control of DexterTM Robot

Kwk Yeung, Omer Faruk Argin, Satoru Okamoto, Paul Saunderson, I. Mackay, Amir M. Ghalamzan E., Wenzhen Yang, Ryan King, Mithun Poozhiyil, Luis G. Uzeda Garcia, Marc Hanheide, Abhishek Mishra, Mike Moulin-Ramsden
article en

Abstract

Robots are essential for carrying out tasks, for example, in a nuclear industry, where direct human involvement is limited. However, present-day nuclear robots are not versatile due to limited autonomy and higher costs. This research presents a merely teleoperated DexterTM nuclear robot’s transformation into an autonomous manipulator for nuclear sort and segregation tasks. The DexterTM system comprises a arm client manipulator designed to operate in extreme radiation environments and a similar single/dual-arm local manipulator. In this paper, initially, a kinematic model and convex optimization-based dynamic model identification of a single-arm DexterTM manipulator is presented. This model is used for autonomous DexterTM control through Robot Operating System (ROS). A new integration framework incorporating vision, AI-based grasp generation and an intelligent radiological surveying method for enhancing the performance of autonomous DexterTM is presented. The efficacy of the framework is demonstrated on a mock-up nuclear waste test-bed using similar waste materials found in the nuclear industry. The experiments performed show potency, generality and applicability of the proposed framework in overcoming the entry barriers for autonomous systems in regulated domains like the nuclear industry.

MachinesVol. 13(3)
University of Surrey (GB), University of Manchester (GB), Faculty of 1000 (United Kingdom) (GB), Manufacturing Technology Centre (United Kingdom) (GB), Coventry (United Kingdom) (GB), Veolia (United Kingdom) (GB), University of Lincoln (GB)
Innovate UK
Openalex Percentile: Top 97%
Robotic Path Planning Algorithms
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