A Framework for Real-Time Autonomous Robotic Sorting and Segregation of Nuclear Waste: Modelling, Identification, and Control of Dexter 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 teleoperated DexterTM nuclear robot’s transformation into an autonomous manipulator for nuclear sort and segregation tasks. The DexterTM system comprises a single/dual 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 and accelerate the adoption of automation without reinventing the wheel.