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Compliant, Large-Strain, and Self-Sensing Twisted String Actuators
- Source :
- Soft Robotics. 9:72-88
- Publication Year :
- 2022
- Publisher :
- Mary Ann Liebert Inc, 2022.
-
Abstract
- Twisted string actuators (TSAs) convert rotational motion from twisting into linear motion. They are known for high energy efficiency, and large linear strain and stress outputs. Although they have been successfully applied as the moving mechanism for different robot applications, their potential in soft robotics is mainly challenged by two aspects: First, the conventional strings of TSAs are stiff and strong but not compliant. Second, precise control of TSAs predominantly relies on external position or force sensors. Because of these, TSA-driven robots are often rigid and bulky. In this study, we propose the design, modeling, and robotic application of TSAs that are compliant, can produce large strain, and are capable of self-sensing during twisting-induced actuation. The design is realized by replacing conventional stiff strings with compliant, thermally activated, and conductive supercoiled polymer strings. Experiments show that the developed TSAs have normalized stiffness of50 N, strain30%, and position self-sensing capability during twisting. The quasi-static actuation and self-sensing properties are accurately captured by the Preisach hysteresis operators. In particular, both the twisting-induced actuation and thermally induced actuation are considered. Finally, the proposed TSAs are successfully demonstrated in a low-cost three-dimensionally printed compliant robotic gripper.
- Subjects :
- 0209 industrial biotechnology
Computer science
Biophysics
Rotation around a fixed axis
Soft robotics
Mechanical engineering
Stiffness
02 engineering and technology
021001 nanoscience & nanotechnology
String (physics)
Computer Science::Robotics
020901 industrial engineering & automation
Artificial Intelligence
Control and Systems Engineering
Position (vector)
Linear motion
medicine
Robot
medicine.symptom
0210 nano-technology
Actuator
Subjects
Details
- ISSN :
- 21695180 and 21695172
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- Soft Robotics
- Accession number :
- edsair.doi.dedup.....816f27830dfeeffd1af2bf81e8dd10db
- Full Text :
- https://doi.org/10.1089/soro.2020.0086