An adaptive framework for robotic polishing based on impedance control

Precise finishing operations such as chamfering and filleting are characterized by relatively low contact forces and low material removal. For such processes, conventional automation approaches like pre-programmed position or force control without adaptations are not suitable to obtain fine surface...

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Main Authors: Lakshminarayanan, Srinivasan, Kana, Sreekanth, Mohan, Dhanya Menoth, Manyar, Omey Mohan, Then, David, Campolo, Domenico
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/155152
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1551522022-07-21T08:50:32Z An adaptive framework for robotic polishing based on impedance control Lakshminarayanan, Srinivasan Kana, Sreekanth Mohan, Dhanya Menoth Manyar, Omey Mohan Then, David Campolo, Domenico School of Mechanical and Aerospace Engineering Rolls-Royce@NTU Corporate Lab Engineering::Mechanical engineering Collaborative Robots Impedance Control Precise finishing operations such as chamfering and filleting are characterized by relatively low contact forces and low material removal. For such processes, conventional automation approaches like pre-programmed position or force control without adaptations are not suitable to obtain fine surface finishing with high profile accuracy. As a result, polishing tasks are still mainly carried out manually by skilled operators. In this paper, we propose an adaptive framework capable of polishing a wide range of materials including hard metals like titanium using a collaborative robot. We propose an iterative learning controller based on impedance control that adapts both position and forces simultaneously in each iteration to regulate the polishing process. The proposed controller can track the desired profile without any a priori knowledge of the forces required to polish different materials. In addition, we introduce a novel mathematical model to generate the complex filleting toolpath based on Lissajous curves. Trials are carried out in finishing tasks such as chamfering and filleting using a collaborative industrial robot to validate the novel framework. Surface roughness and profile measurements show that our adaptive controller can obtain fine polishing output in various materials such as titanium, aluminum, and wood. Ministry of Education (MOE) National Research Foundation (NRF) This project was conducted within the Rolls-Royce@NTU Corporate Lab with support from the National Research Foundation (NRF), Singapore under the Corp Lab@University Scheme. This grant was partly supported by the MOE Tier1 grant (RG48/17). 2022-02-14T07:51:27Z 2022-02-14T07:51:27Z 2021 Journal Article Lakshminarayanan, S., Kana, S., Mohan, D. M., Manyar, O. M., Then, D. & Campolo, D. (2021). An adaptive framework for robotic polishing based on impedance control. International Journal of Advanced Manufacturing Technology, 112(1-2), 401-417. https://dx.doi.org/10.1007/s00170-020-06270-1 0268-3768 https://hdl.handle.net/10356/155152 10.1007/s00170-020-06270-1 2-s2.0-85096369186 1-2 112 401 417 en RG48/17 International Journal of Advanced Manufacturing Technology © 2020 Springer-Verlag London Ltd., part of Springer Nature. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Collaborative Robots
Impedance Control
spellingShingle Engineering::Mechanical engineering
Collaborative Robots
Impedance Control
Lakshminarayanan, Srinivasan
Kana, Sreekanth
Mohan, Dhanya Menoth
Manyar, Omey Mohan
Then, David
Campolo, Domenico
An adaptive framework for robotic polishing based on impedance control
description Precise finishing operations such as chamfering and filleting are characterized by relatively low contact forces and low material removal. For such processes, conventional automation approaches like pre-programmed position or force control without adaptations are not suitable to obtain fine surface finishing with high profile accuracy. As a result, polishing tasks are still mainly carried out manually by skilled operators. In this paper, we propose an adaptive framework capable of polishing a wide range of materials including hard metals like titanium using a collaborative robot. We propose an iterative learning controller based on impedance control that adapts both position and forces simultaneously in each iteration to regulate the polishing process. The proposed controller can track the desired profile without any a priori knowledge of the forces required to polish different materials. In addition, we introduce a novel mathematical model to generate the complex filleting toolpath based on Lissajous curves. Trials are carried out in finishing tasks such as chamfering and filleting using a collaborative industrial robot to validate the novel framework. Surface roughness and profile measurements show that our adaptive controller can obtain fine polishing output in various materials such as titanium, aluminum, and wood.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Lakshminarayanan, Srinivasan
Kana, Sreekanth
Mohan, Dhanya Menoth
Manyar, Omey Mohan
Then, David
Campolo, Domenico
format Article
author Lakshminarayanan, Srinivasan
Kana, Sreekanth
Mohan, Dhanya Menoth
Manyar, Omey Mohan
Then, David
Campolo, Domenico
author_sort Lakshminarayanan, Srinivasan
title An adaptive framework for robotic polishing based on impedance control
title_short An adaptive framework for robotic polishing based on impedance control
title_full An adaptive framework for robotic polishing based on impedance control
title_fullStr An adaptive framework for robotic polishing based on impedance control
title_full_unstemmed An adaptive framework for robotic polishing based on impedance control
title_sort adaptive framework for robotic polishing based on impedance control
publishDate 2022
url https://hdl.handle.net/10356/155152
_version_ 1739837408918110208