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A new approach to improve the parameter estimation accuracy in robotic manipulators using a multi-objective output error identification technique

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A new approach to improve the parameter estimation accuracy in robotic manipulators using a multi-objective output error identification technique. / West, Craig; Montazeri, Allahyar; Monk, Stephen David; Duda, Dobromil; Taylor, Charles James.

26th IEEE International Symposium on Robot and Human Interactive Communication, Lisbon. IEEE, 2017. p. 1406-1411.

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

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West, C, Montazeri, A, Monk, SD, Duda, D & Taylor, CJ 2017, A new approach to improve the parameter estimation accuracy in robotic manipulators using a multi-objective output error identification technique. in 26th IEEE International Symposium on Robot and Human Interactive Communication, Lisbon. IEEE, pp. 1406-1411, 26th IEEE International Symposium on Robot and Human Interactive Communication, Lisbon, Portugal, 28/08/17. https://doi.org/10.1109/ROMAN.2017.8172488

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@inproceedings{2efe9916cab84b119aaba829371142ac,
title = "A new approach to improve the parameter estimation accuracy in robotic manipulators using a multi-objective output error identification technique",
abstract = "The research behind this article primarily concerns the development of mobile robots for nuclear decommissioning. The robotic platform under study has dual, seven-function, hydraulically actuated manipulators, for which the authors have developed a vision based, assisted teleoperation interface for common decommissioning tasks such as pipe cutting. However, to improve safety, task execution speed and operator training-time, high performance control of the nonlinear manipulator dynamics is required. Hence, the present article focuses on an associated dynamic model, and addresses the challenging generic task of parameter estimation for a highly convex and nonlinear system. A novel approach for estimation of the fundamental parameters of the manipulator, based on the idea of multi-objectivization, is proposed. Here, a single objective output error identification problem is converted into a multi-objective optimization problem. This is solved using a multi-objective genetic algorithm with non-dominated sorting. Numerical and experimental results using the nuclear decommissioning robot, show that the performance of the proposed approach, in terms of both the output error index and the accuracy of the estimated parameters, is superior to the previously studied single-objective identification problem.",
author = "Craig West and Allahyar Montazeri and Monk, {Stephen David} and Dobromil Duda and Taylor, {Charles James}",
year = "2017",
month = "12",
day = "14",
doi = "10.1109/ROMAN.2017.8172488",
language = "English",
isbn = "9781538635193",
pages = "1406--1411",
booktitle = "26th IEEE International Symposium on Robot and Human Interactive Communication, Lisbon",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - A new approach to improve the parameter estimation accuracy in robotic manipulators using a multi-objective output error identification technique

AU - West, Craig

AU - Montazeri, Allahyar

AU - Monk, Stephen David

AU - Duda, Dobromil

AU - Taylor, Charles James

PY - 2017/12/14

Y1 - 2017/12/14

N2 - The research behind this article primarily concerns the development of mobile robots for nuclear decommissioning. The robotic platform under study has dual, seven-function, hydraulically actuated manipulators, for which the authors have developed a vision based, assisted teleoperation interface for common decommissioning tasks such as pipe cutting. However, to improve safety, task execution speed and operator training-time, high performance control of the nonlinear manipulator dynamics is required. Hence, the present article focuses on an associated dynamic model, and addresses the challenging generic task of parameter estimation for a highly convex and nonlinear system. A novel approach for estimation of the fundamental parameters of the manipulator, based on the idea of multi-objectivization, is proposed. Here, a single objective output error identification problem is converted into a multi-objective optimization problem. This is solved using a multi-objective genetic algorithm with non-dominated sorting. Numerical and experimental results using the nuclear decommissioning robot, show that the performance of the proposed approach, in terms of both the output error index and the accuracy of the estimated parameters, is superior to the previously studied single-objective identification problem.

AB - The research behind this article primarily concerns the development of mobile robots for nuclear decommissioning. The robotic platform under study has dual, seven-function, hydraulically actuated manipulators, for which the authors have developed a vision based, assisted teleoperation interface for common decommissioning tasks such as pipe cutting. However, to improve safety, task execution speed and operator training-time, high performance control of the nonlinear manipulator dynamics is required. Hence, the present article focuses on an associated dynamic model, and addresses the challenging generic task of parameter estimation for a highly convex and nonlinear system. A novel approach for estimation of the fundamental parameters of the manipulator, based on the idea of multi-objectivization, is proposed. Here, a single objective output error identification problem is converted into a multi-objective optimization problem. This is solved using a multi-objective genetic algorithm with non-dominated sorting. Numerical and experimental results using the nuclear decommissioning robot, show that the performance of the proposed approach, in terms of both the output error index and the accuracy of the estimated parameters, is superior to the previously studied single-objective identification problem.

U2 - 10.1109/ROMAN.2017.8172488

DO - 10.1109/ROMAN.2017.8172488

M3 - Conference contribution/Paper

SN - 9781538635193

SP - 1406

EP - 1411

BT - 26th IEEE International Symposium on Robot and Human Interactive Communication, Lisbon

PB - IEEE

ER -