| Autor: |
Kazuki Higashi, Keisuke Koyama, Ryuta Ozawa, Kazuyuki Nagata, Takuya Kiyokawa, Weiwei Wan, Kensuke Harada |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 11, Pp 129258-129268 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2023.3333385 |
| Popis: |
Soft multi-fingered robotic hands are safe in human environments and can perform human-like behaviors. However, structural complexities and nonlinearities in soft actuators complicate torque sensing, a critical function for dexterous object manipulation. This study introduces a torque-sensing finger joint mechanism using a soft actuator composed of water-powered hydraulic bellows. Two real-time torque estimation methods are proposed, developed, and validated specifically for cases in which buckling occurs in the bellows, a situation that typically presents significant estimation challenges. The buckling spring model for torque estimation, explicitly considering the buckling effect, is a linear model that considers two elastic forces for the pressure and external force. The multi-layer perceptron model for torque estimation considers the nonlinearity of the actuator. The experimental results show that both methods can estimate the torque in real-time with high accuracy. The torque control for grasping fragile objects has also been examined in real-world scenarios. The findings indicate that, compared to the approach without torque control, successful and safe manipulation of the target objects is accomplished without causing detrimental deformation. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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