Estimating human wrist stiffness during a tooling task
In this work, we propose a practical approach to estimate human joint stiffness during tooling tasks for the purpose of programming a robot by demonstration. More specifically, we estimate the stiffness along the wrist radial-ulnar deviation while a human operator performs flexion-extension movement...
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sg-ntu-dr.10356-1456852023-03-04T17:23:52Z Estimating human wrist stiffness during a tooling task Phan, Gia-Hoang Hansen, Clint Tommasino, Paolo Budhota, Aamani Mohan, Dhanya Menoth Hussain, Asif Burdet, Etienne Campolo, Domenico School of Mechanical and Aerospace Engineering Robotics Research Centre Engineering::Mechanical engineering Instrumented Tool Tool-workpiece Interaction In this work, we propose a practical approach to estimate human joint stiffness during tooling tasks for the purpose of programming a robot by demonstration. More specifically, we estimate the stiffness along the wrist radial-ulnar deviation while a human operator performs flexion-extension movements during a polishing task. The joint stiffness information allows to transfer skills from expert human operators to industrial robots. A typical hand-held, abrasive tool used by humans during finishing tasks was instrumented at the handle (through which both robots and humans are attached to the tool) to assess the 3D force/torque interactions between operator and tool during finishing task, as well as the 3D kinematics of the tool itself. Building upon stochastic methods for human arm impedance estimation, the novelty of our approach is that we rely on the natural variability taking place during the multi-passes task itself to estimate (neuro-)mechanical impedance during motion. Our apparatus (hand-held, finishing tool instrumented with motion capture and multi-axis force/torque sensors) and algorithms (for filtering and impedance estimation) were first tested on an impedance-controlled industrial robot carrying out the finishing task of interest, where the impedance could be pre-programmed. We were able to accurately estimate impedance in this case. The same apparatus and algorithms were then applied to the same task performed by a human operators. The stiffness values of the human operator, at different force level, correlated positively with the muscular activity, measured during the same task. Ministry of Education (MOE) Published version The work was supported by the MOE Tier1 grant (RG48/17), Singapore. EB is funded in part by the EU-FP7 grants BALANCE (ICT-601003), SYMBITRON (ICT-661626) and EU-H2020 grant COGIMON (ICT-23-2014). We acknowledge financial support by DFG within the funding programme Open Access Publizieren. 2021-01-05T02:00:16Z 2021-01-05T02:00:16Z 2020 Journal Article Phan, G.-H., Hansen, C., Tommasino, P., Budhota, A., Mohan, D. M., Hussain, A., . . . Campolo, D. (2020). Estimating human wrist stiffness during a tooling task. Sensors, 20(11), 3260-. doi:10.3390/s20113260 1424-8220 https://hdl.handle.net/10356/145685 10.3390/s20113260 32521678 11 20 en RG48/17 Sensors © 2020 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). application/pdf |
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Engineering::Mechanical engineering Instrumented Tool Tool-workpiece Interaction Phan, Gia-Hoang Hansen, Clint Tommasino, Paolo Budhota, Aamani Mohan, Dhanya Menoth Hussain, Asif Burdet, Etienne Campolo, Domenico Estimating human wrist stiffness during a tooling task |
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In this work, we propose a practical approach to estimate human joint stiffness during tooling tasks for the purpose of programming a robot by demonstration. More specifically, we estimate the stiffness along the wrist radial-ulnar deviation while a human operator performs flexion-extension movements during a polishing task. The joint stiffness information allows to transfer skills from expert human operators to industrial robots. A typical hand-held, abrasive tool used by humans during finishing tasks was instrumented at the handle (through which both robots and humans are attached to the tool) to assess the 3D force/torque interactions between operator and tool during finishing task, as well as the 3D kinematics of the tool itself. Building upon stochastic methods for human arm impedance estimation, the novelty of our approach is that we rely on the natural variability taking place during the multi-passes task itself to estimate (neuro-)mechanical impedance during motion. Our apparatus (hand-held, finishing tool instrumented with motion capture and multi-axis force/torque sensors) and algorithms (for filtering and impedance estimation) were first tested on an impedance-controlled industrial robot carrying out the finishing task of interest, where the impedance could be pre-programmed. We were able to accurately estimate impedance in this case. The same apparatus and algorithms were then applied to the same task performed by a human operators. The stiffness values of the human operator, at different force level, correlated positively with the muscular activity, measured during the same task. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Phan, Gia-Hoang Hansen, Clint Tommasino, Paolo Budhota, Aamani Mohan, Dhanya Menoth Hussain, Asif Burdet, Etienne Campolo, Domenico |
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Article |
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Phan, Gia-Hoang Hansen, Clint Tommasino, Paolo Budhota, Aamani Mohan, Dhanya Menoth Hussain, Asif Burdet, Etienne Campolo, Domenico |
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Phan, Gia-Hoang |
title |
Estimating human wrist stiffness during a tooling task |
title_short |
Estimating human wrist stiffness during a tooling task |
title_full |
Estimating human wrist stiffness during a tooling task |
title_fullStr |
Estimating human wrist stiffness during a tooling task |
title_full_unstemmed |
Estimating human wrist stiffness during a tooling task |
title_sort |
estimating human wrist stiffness during a tooling task |
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2021 |
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https://hdl.handle.net/10356/145685 |
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