Trigger-Based Dexterous Operation with Multimodal Sensors for Soft Robotic Hand
This paper focuses on how to improve the operation ability of a soft robotic hand (SRH). A trigger-based dexterous operation (TDO) strategy with multimodal sensors is proposed to perform autonomous choice operations. The multimodal sensors include optical-based fiber curvature sensor (OFCS), gas pre...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/19/8978 |
| _version_ | 1797516885243199488 |
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| author | Haiming Huang Junhao Lin Linyuan Wu Zhenkun Wen Mingjie Dong |
| author_facet | Haiming Huang Junhao Lin Linyuan Wu Zhenkun Wen Mingjie Dong |
| author_sort | Haiming Huang |
| collection | DOAJ |
| description | This paper focuses on how to improve the operation ability of a soft robotic hand (SRH). A trigger-based dexterous operation (TDO) strategy with multimodal sensors is proposed to perform autonomous choice operations. The multimodal sensors include optical-based fiber curvature sensor (OFCS), gas pressure sensor (GPS), capacitive pressure contact sensor (CPCS), and resistance pressure contact sensor (RPCS). The OFCS embedded in the soft finger and the GPS series connected in the gas channel are used to detect the curvature of the finger. The CPCS attached on the fingertip and the RPCS attached on the palm are employed to detect the touch force. The framework of TDO is divided into sensor detection and action operation. Hardware layer, information acquisition layer, and decision layer form the sensor detection module; action selection layer, actuator drive layer, and hardware layer constitute the action operation module. An autonomous choice decision unit is used to connect the sensor detecting module and action operation module. The experiment results reveal that the TDO algorithm is effective and feasible, and the actions of grasping plastic framework, pinching roller ball pen and screwdriver, and handshake are executed exactly. |
| first_indexed | 2024-03-10T07:07:07Z |
| format | Article |
| id | doaj.art-d70fbb5dc1244d8281942127952b5145 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T07:07:07Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-d70fbb5dc1244d8281942127952b51452023-11-22T15:45:55ZengMDPI AGApplied Sciences2076-34172021-09-011119897810.3390/app11198978Trigger-Based Dexterous Operation with Multimodal Sensors for Soft Robotic HandHaiming Huang0Junhao Lin1Linyuan Wu2Zhenkun Wen3Mingjie Dong4College of Electronics and Information Engineering, Shenzhen University, Shenzhen 518060, ChinaCollege of Electronics and Information Engineering, Shenzhen University, Shenzhen 518060, ChinaCollege of Electronics and Information Engineering, Shenzhen University, Shenzhen 518060, ChinaCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaFaculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, ChinaThis paper focuses on how to improve the operation ability of a soft robotic hand (SRH). A trigger-based dexterous operation (TDO) strategy with multimodal sensors is proposed to perform autonomous choice operations. The multimodal sensors include optical-based fiber curvature sensor (OFCS), gas pressure sensor (GPS), capacitive pressure contact sensor (CPCS), and resistance pressure contact sensor (RPCS). The OFCS embedded in the soft finger and the GPS series connected in the gas channel are used to detect the curvature of the finger. The CPCS attached on the fingertip and the RPCS attached on the palm are employed to detect the touch force. The framework of TDO is divided into sensor detection and action operation. Hardware layer, information acquisition layer, and decision layer form the sensor detection module; action selection layer, actuator drive layer, and hardware layer constitute the action operation module. An autonomous choice decision unit is used to connect the sensor detecting module and action operation module. The experiment results reveal that the TDO algorithm is effective and feasible, and the actions of grasping plastic framework, pinching roller ball pen and screwdriver, and handshake are executed exactly.https://www.mdpi.com/2076-3417/11/19/8978dexterous operationmultimodal sensorshuman–robot interactionautonomous choice decisionsoft robotic hand |
| spellingShingle | Haiming Huang Junhao Lin Linyuan Wu Zhenkun Wen Mingjie Dong Trigger-Based Dexterous Operation with Multimodal Sensors for Soft Robotic Hand Applied Sciences dexterous operation multimodal sensors human–robot interaction autonomous choice decision soft robotic hand |
| title | Trigger-Based Dexterous Operation with Multimodal Sensors for Soft Robotic Hand |
| title_full | Trigger-Based Dexterous Operation with Multimodal Sensors for Soft Robotic Hand |
| title_fullStr | Trigger-Based Dexterous Operation with Multimodal Sensors for Soft Robotic Hand |
| title_full_unstemmed | Trigger-Based Dexterous Operation with Multimodal Sensors for Soft Robotic Hand |
| title_short | Trigger-Based Dexterous Operation with Multimodal Sensors for Soft Robotic Hand |
| title_sort | trigger based dexterous operation with multimodal sensors for soft robotic hand |
| topic | dexterous operation multimodal sensors human–robot interaction autonomous choice decision soft robotic hand |
| url | https://www.mdpi.com/2076-3417/11/19/8978 |
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