Abstract
This paper describes a novel automatic solution for tool-changing operations using dexterous teleoperated robots in a nuclear glovebox. This solution can identify and locate tools in the nuclear glovebox by visually tracking augmented reality (AR) tags online at a low computational cost. The solution is designed in a modular manner taking into account different practical constraints, so it can be easily adapted to enormous existing nuclear gloveboxes. In practice, the proposed solution is introduced to an existing robotic system including two teleoperated lightweight manipulators in a nuclear glovebox. The experimental tests have demonstrated the effectiveness of the automated tool-changing solution without any knowledge of the mock-up environment a priori.
We would like to thank UK Research and Innovation (UKRI) for their support and funding that has come from the Robotics and Artificial Intelligence in Nuclear (RAIN) grant EP/R026084/1. This work has been part-funded by the EPSRC Energy Programme (grant number EP/W006839/1). To obtain further information on the data and models underlying this paper please contact PublicationsManager@ukaea.uk.
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Blake, J., Burroughes, G., Zhang, K. (2022). Automatic, Vision-Based Tool Changing Solution for Dexterous Teleoperation Robots in a Nuclear Glovebox. In: Pacheco-Gutierrez, S., Cryer, A., Caliskanelli, I., Tugal, H., Skilton, R. (eds) Towards Autonomous Robotic Systems. TAROS 2022. Lecture Notes in Computer Science(), vol 13546. Springer, Cham. https://doi.org/10.1007/978-3-031-15908-4_24
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