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Manipulating airflow is important for controlling pneumatically actuated soft robots, however, current switching techniques suffer from leakage under high pressure (>200 kPa) or require a complex fabrication process. We propose a new method for reliably and repeatably cutting off airflow by harnessing pre-loaded torsional forces applied to our tubing. The switching distance and hysteresis of our pre-twisted tubing are programmable by varying the tube length and the twisting angle. Our experiments demonstrate the use of pretwisted tubing to implement CMOS equivalent fluidic switches configured as NOT-, AND-, and OR-gates, and a distance sensor for feedback control for the oscillation of a PneuNet. Our approach of pre-loading tubes with a torsional force allows for simplicity, integrated functionality, and the capability of manipulating high-pressure, fluidic signals mainly at the cost of tubing.
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FDM‐Printed CMOS Logic Gates from Flexing Beam Mechanisms for the Control of Soft Robotic Systems
Fluidic control systems target unique applications where conventional electronics fail. However, current fluidic control systems face challenges in accessible fabrication, reproducibility, and modifiable characteristics such as operating pressure and instability count. Herein, fused deposition‐modeled compliant mechanisms with flexing beams and soft linear actuators for fluid switching and the control of soft robotic systems are introduced. A linear actuator switches a compliant mechanism to cut off airflow through off‐the‐shelf tubing. The modular compliant logic devices can be configured as normally open or normally closed switches, as NOT, AND, and OR gates, and as nonvolatile memory elements. Their use is demonstrated in controlling a fluidic stepper motor, a worm‐like robot, and a fluidic display. These fluidic switches are printable using inexpensive desktop 3D printers, can be reliably reproduced in large quantities, and offer a wide range of modifiable parameters, including scalability, adaptability in operating pressure, and the tunability of instability counts for computational and memory functions.
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- Award ID(s):
- 2512999
- PAR ID:
- 10556530
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Intelligent Systems
- Volume:
- 7
- Issue:
- 2
- ISSN:
- 2640-4567
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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