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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Towards a Cooperative Robotic System for Autonomous Pipe Cutting in Nuclear Decommissioning
AU - Burrell, Thomas Ian
AU - West, Craig
AU - Monk, Stephen David
AU - Montazeri, Allahyar
AU - Taylor, C. James
N1 - ©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PY - 2018/9/5
Y1 - 2018/9/5
N2 - A mobile camera is used to support an assisted teleoperation pipe–cutting system for nuclear decommissioning. The base system consists of dual–manipulators with a single mounted Kinect camera. The user selects the object from an on–screen image, whilst the computer control system automatically grasps the pipe with one end–effector and positions the second for cutting. However, the system fails in some cases because of data limitations, for example a partially obscured pipe in a challenging decommissioning scenario (simulated in the laboratory). Hence, the present article develops a new method to increase the use case scenarios via the introduction of mobile cameras e.g. for mounting on a drone. This is a non-trivial problem, with SLAM and ArUco fiducials introduced to locate the cameras, and a novel error correction method proposed for finding the ArUco markers. Preliminary results demonstrate the validity of the approach but improvements will be required for robust autonomous cutting. Hence, to reduce the pipe position estimation errors, suggestions are made for various algorithmic and hardware refinements.
AB - A mobile camera is used to support an assisted teleoperation pipe–cutting system for nuclear decommissioning. The base system consists of dual–manipulators with a single mounted Kinect camera. The user selects the object from an on–screen image, whilst the computer control system automatically grasps the pipe with one end–effector and positions the second for cutting. However, the system fails in some cases because of data limitations, for example a partially obscured pipe in a challenging decommissioning scenario (simulated in the laboratory). Hence, the present article develops a new method to increase the use case scenarios via the introduction of mobile cameras e.g. for mounting on a drone. This is a non-trivial problem, with SLAM and ArUco fiducials introduced to locate the cameras, and a novel error correction method proposed for finding the ArUco markers. Preliminary results demonstrate the validity of the approach but improvements will be required for robust autonomous cutting. Hence, to reduce the pipe position estimation errors, suggestions are made for various algorithmic and hardware refinements.
KW - Cooperative Robotics
KW - Nuclear Decommissioning
KW - Computer Vision
KW - ArUco Fiducials
KW - OpenCV
KW - SLAM
KW - Kinect
U2 - 10.1109/CONTROL.2018.8516841
DO - 10.1109/CONTROL.2018.8516841
M3 - Conference contribution/Paper
SN - 9781509064113
SP - 283
EP - 288
BT - 2018 UKACC 12th International Conference on Control (CONTROL)
PB - IEEE
T2 - 12th UKACC International Conference on Control
Y2 - 5 September 2018 through 7 September 2018
ER -