Teleoperation Control of an Underactuated Bionic Hand: Comparison between Wearable and Vision-Tracking-Based Methods
Bionic hands have been employed in a wide range of applications, including prosthetics, robotic grasping, and human–robot interaction. However, considering the underactuated and nonlinear characteristics, as well as the mechanical structure’s backlash, achieving natural and intuitive teleoperation c...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Robotics |
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| Online Access: | https://www.mdpi.com/2218-6581/11/3/61 |
| _version_ | 1797482587216674816 |
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| author | Junling Fu Massimiliano Poletti Qingsheng Liu Elisa Iovene Hang Su Giancarlo Ferrigno Elena De Momi |
| author_facet | Junling Fu Massimiliano Poletti Qingsheng Liu Elisa Iovene Hang Su Giancarlo Ferrigno Elena De Momi |
| author_sort | Junling Fu |
| collection | DOAJ |
| description | Bionic hands have been employed in a wide range of applications, including prosthetics, robotic grasping, and human–robot interaction. However, considering the underactuated and nonlinear characteristics, as well as the mechanical structure’s backlash, achieving natural and intuitive teleoperation control of an underactuated bionic hand remains a critical issue. In this paper, the teleoperation control of an underactuated bionic hand using wearable and vision-tracking system-based methods is investigated. Firstly, the nonlinear behaviour of the bionic hand is observed and the kinematics model is formulated. Then, the wearable-glove-based and the vision-tracking-based teleoperation control frameworks are implemented, respectively. Furthermore, experiments are conducted to demonstrate the feasibility and performance of these two methods in terms of accuracy in both static and dynamic scenarios. Finally, a user study and demonstration experiments are conducted to verify the performance of these two approaches in grasp tasks. Both developed systems proved to be exploitable in both powered and precise grasp tasks using the underactuated bionic hand, with a success rate of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>98.6</mn><mo>%</mo></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>96.5</mn><mo>%</mo></mrow></semantics></math></inline-formula>, respectively. The glove-based method turned out to be more accurate and better performing than the vision-based one, but also less comfortable, requiring greater effort by the user. By further incorporating a robot manipulator, the system can be utilised to perform grasp, delivery, or handover tasks in daily, risky, and infectious scenarios. |
| first_indexed | 2024-03-09T22:34:32Z |
| format | Article |
| id | doaj.art-203eab6d9146499fad6a5c5b8fe28470 |
| institution | Directory Open Access Journal |
| issn | 2218-6581 |
| language | English |
| last_indexed | 2024-03-09T22:34:32Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Robotics |
| spelling | doaj.art-203eab6d9146499fad6a5c5b8fe284702023-11-23T18:50:23ZengMDPI AGRobotics2218-65812022-05-011136110.3390/robotics11030061Teleoperation Control of an Underactuated Bionic Hand: Comparison between Wearable and Vision-Tracking-Based MethodsJunling Fu0Massimiliano Poletti1Qingsheng Liu2Elisa Iovene3Hang Su4Giancarlo Ferrigno5Elena De Momi6Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, ItalyBionic hands have been employed in a wide range of applications, including prosthetics, robotic grasping, and human–robot interaction. However, considering the underactuated and nonlinear characteristics, as well as the mechanical structure’s backlash, achieving natural and intuitive teleoperation control of an underactuated bionic hand remains a critical issue. In this paper, the teleoperation control of an underactuated bionic hand using wearable and vision-tracking system-based methods is investigated. Firstly, the nonlinear behaviour of the bionic hand is observed and the kinematics model is formulated. Then, the wearable-glove-based and the vision-tracking-based teleoperation control frameworks are implemented, respectively. Furthermore, experiments are conducted to demonstrate the feasibility and performance of these two methods in terms of accuracy in both static and dynamic scenarios. Finally, a user study and demonstration experiments are conducted to verify the performance of these two approaches in grasp tasks. Both developed systems proved to be exploitable in both powered and precise grasp tasks using the underactuated bionic hand, with a success rate of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>98.6</mn><mo>%</mo></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>96.5</mn><mo>%</mo></mrow></semantics></math></inline-formula>, respectively. The glove-based method turned out to be more accurate and better performing than the vision-based one, but also less comfortable, requiring greater effort by the user. By further incorporating a robot manipulator, the system can be utilised to perform grasp, delivery, or handover tasks in daily, risky, and infectious scenarios.https://www.mdpi.com/2218-6581/11/3/61bionic handteleoperation controlhuman–robot interactionwearable glovevision tracking |
| spellingShingle | Junling Fu Massimiliano Poletti Qingsheng Liu Elisa Iovene Hang Su Giancarlo Ferrigno Elena De Momi Teleoperation Control of an Underactuated Bionic Hand: Comparison between Wearable and Vision-Tracking-Based Methods Robotics bionic hand teleoperation control human–robot interaction wearable glove vision tracking |
| title | Teleoperation Control of an Underactuated Bionic Hand: Comparison between Wearable and Vision-Tracking-Based Methods |
| title_full | Teleoperation Control of an Underactuated Bionic Hand: Comparison between Wearable and Vision-Tracking-Based Methods |
| title_fullStr | Teleoperation Control of an Underactuated Bionic Hand: Comparison between Wearable and Vision-Tracking-Based Methods |
| title_full_unstemmed | Teleoperation Control of an Underactuated Bionic Hand: Comparison between Wearable and Vision-Tracking-Based Methods |
| title_short | Teleoperation Control of an Underactuated Bionic Hand: Comparison between Wearable and Vision-Tracking-Based Methods |
| title_sort | teleoperation control of an underactuated bionic hand comparison between wearable and vision tracking based methods |
| topic | bionic hand teleoperation control human–robot interaction wearable glove vision tracking |
| url | https://www.mdpi.com/2218-6581/11/3/61 |
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