A methodology to model and simulate customized realistic anthropomorphic robotic hands

When building robotic hands, researchers are always face with two main issues of how to make robotic hands look human-like and how to make robotic hands function like real hands. Most existing solutions solve these issues by manually modelling the robotic hand [10-18]. However, the design processes...

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Main Authors: Tian, Li, Magnenat-Thalmann, Nadia, Thalmann, Daniel, Zheng, Jianmin
Other Authors: School of Computer Science and Engineering
Format: Conference Paper
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/138936
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author Tian, Li
Magnenat-Thalmann, Nadia
Thalmann, Daniel
Zheng, Jianmin
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Tian, Li
Magnenat-Thalmann, Nadia
Thalmann, Daniel
Zheng, Jianmin
author_sort Tian, Li
collection NTU
description When building robotic hands, researchers are always face with two main issues of how to make robotic hands look human-like and how to make robotic hands function like real hands. Most existing solutions solve these issues by manually modelling the robotic hand [10-18]. However, the design processes are long, and it is difficult to duplicate the geometry shape of a human hand. To solve these two issues, this paper presents a simple and effective method that combines 3D printing and digitization techniques to create a 3D printable cable-driven robotic hand from scanning a physical hand. The method involves segmenting the 3D scanned hand model, adding joints, and converting it into a 3D printable model. Comparing to other robotic solutions, our solution retains more than 90% geometry information of a human hand1, which is attained from 3D scanning. Our modelling progress takes around 15 minutes that include 10 minutes of 3D scanning and five minutes for changing the scanned model to an articulated model by running our algorithm. Compared to other articulated modelling solutions [19, 20], our solution is compatible with an actuation system which provides our robotic hand with the ability to mimic different gestures. We have also developed a way of representing hand skeletons based on the hand anthropometric. As a proof of concept, we demonstrate our robotic hand's performance in the grasping experiments.
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spelling ntu-10356/1389362020-09-26T21:53:04Z A methodology to model and simulate customized realistic anthropomorphic robotic hands Tian, Li Magnenat-Thalmann, Nadia Thalmann, Daniel Zheng, Jianmin School of Computer Science and Engineering CGI 2018: Proceedings of Computer Graphics International 2018 Institute for Media Innovation (IMI) Engineering::Computer science and engineering Robotics Embedded Systems When building robotic hands, researchers are always face with two main issues of how to make robotic hands look human-like and how to make robotic hands function like real hands. Most existing solutions solve these issues by manually modelling the robotic hand [10-18]. However, the design processes are long, and it is difficult to duplicate the geometry shape of a human hand. To solve these two issues, this paper presents a simple and effective method that combines 3D printing and digitization techniques to create a 3D printable cable-driven robotic hand from scanning a physical hand. The method involves segmenting the 3D scanned hand model, adding joints, and converting it into a 3D printable model. Comparing to other robotic solutions, our solution retains more than 90% geometry information of a human hand1, which is attained from 3D scanning. Our modelling progress takes around 15 minutes that include 10 minutes of 3D scanning and five minutes for changing the scanned model to an articulated model by running our algorithm. Compared to other articulated modelling solutions [19, 20], our solution is compatible with an actuation system which provides our robotic hand with the ability to mimic different gestures. We have also developed a way of representing hand skeletons based on the hand anthropometric. As a proof of concept, we demonstrate our robotic hand's performance in the grasping experiments. NRF (Natl Research Foundation, S’pore) Accepted version 2020-05-14T04:09:51Z 2020-05-14T04:09:51Z 2018 Conference Paper Tian, L., Magnenat-Thalmann, N., Thalmann, D., & Zheng, J. (2018). A methodology to model and simulate customized realistic anthropomorphic robotic hands. Proceedings of Computer Graphics International 2018, 153-162. doi:10.1145/3208159.3208182 https://hdl.handle.net/10356/138936 10.1145/3208159.3208182 153 162 en © 2018 Association for Computing Machinery. All rights reserved. This paper was published in CGI 2018: Proceedings of Computer Graphics International 2018 and is made available with permission of Association for Computing Machinery. application/pdf
spellingShingle Engineering::Computer science and engineering
Robotics
Embedded Systems
Tian, Li
Magnenat-Thalmann, Nadia
Thalmann, Daniel
Zheng, Jianmin
A methodology to model and simulate customized realistic anthropomorphic robotic hands
title A methodology to model and simulate customized realistic anthropomorphic robotic hands
title_full A methodology to model and simulate customized realistic anthropomorphic robotic hands
title_fullStr A methodology to model and simulate customized realistic anthropomorphic robotic hands
title_full_unstemmed A methodology to model and simulate customized realistic anthropomorphic robotic hands
title_short A methodology to model and simulate customized realistic anthropomorphic robotic hands
title_sort methodology to model and simulate customized realistic anthropomorphic robotic hands
topic Engineering::Computer science and engineering
Robotics
Embedded Systems
url https://hdl.handle.net/10356/138936
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