Home > Research > Publications & Outputs > Towards a Cooperative Robotic System for Autono...

Electronic data

  • 18ukacc_coop_robot

    Rights statement: ©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.

    Accepted author manuscript, 434 KB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

Links

Text available via DOI:

View graph of relations

Towards a Cooperative Robotic System for Autonomous Pipe Cutting in Nuclear Decommissioning

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

Published

Standard

Towards a Cooperative Robotic System for Autonomous Pipe Cutting in Nuclear Decommissioning. / Burrell, Thomas Ian; West, Craig; Monk, Stephen David; Montazeri, Allahyar; Taylor, C. James.

2018 UKACC 12th International Conference on Control (CONTROL). IEEE, 2018. p. 283-288.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

Harvard

Burrell, TI, West, C, Monk, SD, Montazeri, A & Taylor, CJ 2018, Towards a Cooperative Robotic System for Autonomous Pipe Cutting in Nuclear Decommissioning. in 2018 UKACC 12th International Conference on Control (CONTROL). IEEE, pp. 283-288, 12th UKACC International Conference on Control, Sheffield, United Kingdom, 5/09/18. https://doi.org/10.1109/CONTROL.2018.8516841

APA

Vancouver

Author

Bibtex

@inproceedings{1afa7f75e7034d4cb4d7cda55a19e0fe,
title = "Towards a Cooperative Robotic System for Autonomous Pipe Cutting in Nuclear Decommissioning",
abstract = "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.",
keywords = "Cooperative Robotics, Nuclear Decommissioning, Computer Vision, ArUco Fiducials, OpenCV, SLAM, Kinect",
author = "Burrell, {Thomas Ian} and Craig West and Monk, {Stephen David} and Allahyar Montazeri and Taylor, {C. James}",
note = "{\textcopyright}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.; 12th UKACC International Conference on Control ; Conference date: 05-09-2018 Through 07-09-2018",
year = "2018",
month = sep
day = "5",
doi = "10.1109/CONTROL.2018.8516841",
language = "English",
isbn = "9781509064113",
pages = "283--288",
booktitle = "2018 UKACC 12th International Conference on Control (CONTROL)",
publisher = "IEEE",
url = "https://control2018.group.shef.ac.uk/",

}

RIS

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 -