Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke Measurement
The size of a device and its adaptability to human properties are important factors in developing a wearable device. In wearable robot research, therefore, soft materials and tendon transmissions have been utilized to make robots compact and adaptable to the human body. However, when used for wearab...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/10/2852 |
| _version_ | 1797567749467144192 |
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| author | Byungchul Kim Jiwon Ryu Kyu-Jin Cho |
| author_facet | Byungchul Kim Jiwon Ryu Kyu-Jin Cho |
| author_sort | Byungchul Kim |
| collection | DOAJ |
| description | The size of a device and its adaptability to human properties are important factors in developing a wearable device. In wearable robot research, therefore, soft materials and tendon transmissions have been utilized to make robots compact and adaptable to the human body. However, when used for wearable robots, these methods sometimes cause uncertainties that originate from elongation of the soft material or from undefined human properties. In this research, to consider these uncertainties, we propose a data-driven method that identifies both kinematic and stiffness parameters using tension and wire stroke of the actuators. Through kinematic identification, a method is proposed to find the exact joint position as a function of the joint angle. Through stiffness identification, the relationship between the actuation force and the joint angle is obtained using Gaussian Process Regression (GPR). As a result, by applying the proposed method to a specific robot, the research outlined in this paper verifies how the proposed method can be used in wearable robot applications. This work examines a novel wearable robot named Exo-Index, which assists a human’s index finger through the use of three actuators. The proposed identification methods enable control of the wearable robot to result in appropriate postures for grasping objects of different shapes and sizes. |
| first_indexed | 2024-03-10T19:46:54Z |
| format | Article |
| id | doaj.art-9efd97c9ad564488bd373f7fb2e19257 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T19:46:54Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9efd97c9ad564488bd373f7fb2e192572023-11-20T00:45:31ZengMDPI AGSensors1424-82202020-05-012010285210.3390/s20102852Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke MeasurementByungchul Kim0Jiwon Ryu1Kyu-Jin Cho2Biorobotics Laboratory, School of Mechanical and Aerospace Engineering, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, KoreaBiorobotics Laboratory, School of Mechanical and Aerospace Engineering, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, KoreaBiorobotics Laboratory, School of Mechanical and Aerospace Engineering, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, KoreaThe size of a device and its adaptability to human properties are important factors in developing a wearable device. In wearable robot research, therefore, soft materials and tendon transmissions have been utilized to make robots compact and adaptable to the human body. However, when used for wearable robots, these methods sometimes cause uncertainties that originate from elongation of the soft material or from undefined human properties. In this research, to consider these uncertainties, we propose a data-driven method that identifies both kinematic and stiffness parameters using tension and wire stroke of the actuators. Through kinematic identification, a method is proposed to find the exact joint position as a function of the joint angle. Through stiffness identification, the relationship between the actuation force and the joint angle is obtained using Gaussian Process Regression (GPR). As a result, by applying the proposed method to a specific robot, the research outlined in this paper verifies how the proposed method can be used in wearable robot applications. This work examines a novel wearable robot named Exo-Index, which assists a human’s index finger through the use of three actuators. The proposed identification methods enable control of the wearable robot to result in appropriate postures for grasping objects of different shapes and sizes.https://www.mdpi.com/1424-8220/20/10/2852soft wearable robotrobotic systems parameter estimationjoint angle estimationdata-driven control |
| spellingShingle | Byungchul Kim Jiwon Ryu Kyu-Jin Cho Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke Measurement Sensors soft wearable robot robotic systems parameter estimation joint angle estimation data-driven control |
| title | Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke Measurement |
| title_full | Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke Measurement |
| title_fullStr | Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke Measurement |
| title_full_unstemmed | Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke Measurement |
| title_short | Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke Measurement |
| title_sort | joint angle estimation of a tendon driven soft wearable robot through a tension and stroke measurement |
| topic | soft wearable robot robotic systems parameter estimation joint angle estimation data-driven control |
| url | https://www.mdpi.com/1424-8220/20/10/2852 |
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