Research Papers

Electromechanical Control and Stability Analysis of a Soft Swim-Bladder Robot Driven by Dielectric Elastomer

[+] Author and Article Information
Bangyuan Liu

College of Control Science and Engineering,
Zhejiang University,
38 Zheda Road,
Hangzhou 310027, China
e-mail: bennyliu@zju.edu.cn

Feiyu Chen

College of Mechanical Engineering,
Zhejiang University,
38 Zheda Road,
Hangzhou 310027, China
e-mail: feiyuchen@zju.edu.cn

Sukai Wang

College of Biomedical Engineering and
Instrument Science,
Zhejiang University,
38 Zheda Road,
Hangzhou 310027, China
e-mail: wangsukai@zju.edu.cn

Zhiqiang Fu

College of Mechanical Engineering,
Zhejiang University,
38 Zheda Road,
Hangzhou 310027, China
e-mail: zhiqiangfu@zju.edu.cn

Tingyu Cheng

Jonh A. Paulson School of Engineering and
Applied Sciences,
Harvard University,
Cambridge, MA 02138
e-mail: tingyucheng@g.harvard.edu

Tiefeng Li

Department of Engineering Mechanics,
Key Laboratory of Soft Machines and
Smart Devices of Zhejiang Province,
Soft Matter Research Center (SMRC),
Zhejiang University,
38 Zheda Road,
Hangzhou 310027, China
e-mail: litiefeng@zju.edu.cn

Contributed by the Applied Mechanics Division of ASME for publication in the JOURNAL OF APPLIED MECHANICS. Manuscript received April 25, 2017; final manuscript received June 20, 2017; published online July 12, 2017. Assoc. Editor: Kyung-Suk Kim.

J. Appl. Mech 84(9), 091005 (Jul 12, 2017) (9 pages) Paper No: JAM-17-1219; doi: 10.1115/1.4037147 History: Received April 25, 2017; Revised June 20, 2017

Compared to the conventional rigid robots, the soft robots driven by soft active materials possess unique advantages with their high adaptability in field exploration and seamless interaction with human. As one type of soft robot, soft aquatic robots play important roles in the application of ocean exploration and engineering. However, the soft robots still face grand challenges, such as high mobility, environmental tolerance, and accurate control. Here, we design a soft robot with a fully integrated onboard system including power and wireless communication. Without any motor, dielectric elastomer (DE) membrane with a balloonlike shape in the soft robot can deform with large actuation, changing the total volume and buoyant force of the robot. With the help of pressure sensor, the robot can move to and stabilize at a designated depth by a closed-loop control. The performance of the robot has been investigated both experimentally and theoretically. Numerical results from the analysis agree well with the results from the experiments. The mechanisms of actuation and control may guide the further design of soft robot and smart devices.

Copyright © 2017 by ASME
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Grahic Jump Location
Fig. 1

Fabrication of controllable artificial swim bladder robot. (a) A DE membrane (stacked VHB membrane with the initial thickness of 2 mm) was biaxially prestretched (3 × 3) on the ABS frame. (b) Carbon grease was coated with a circular shape on one side of the membrane. (c) The prestretched DE membrane was assembled on the top of the acrylic chamber with the carbon grease coated side facing downward. (d) Seal the chamber and add counterweight to balance the buoyant force. (e) The air is pumped into the chamber deforming the DE membrane into a balloon shape.

Grahic Jump Location
Fig. 2

Actuation mechanism of the artificial swim bladder robot. (a) In the inflated state, the DE membrane was deformed by the pressure difference with no voltage applied. (b) Inthe actuated state, a high voltage is applied to the DE membrane. The electric field drives the ions in the surrounding water and electrons in the carbon grease. Positive and negative charges accumulated on both sides of the DE membrane, inducing Maxwell stress and deforming the DE membrane. In the experiment with wired high voltage source, (c) the inflated balloon and chamber with a fixed total volume and buoyant force reach equilibrium at a certain depth under water. (d) The DE membrane was actuated by high voltage. The volume and the buoyant force of the balloon increase. The robot floats up.

Grahic Jump Location
Fig. 3

The onboard power source (Epod) and the method of control and communication. (a) Onboard high voltage source is powered by a lithium–ion battery (3.7 V) with fly back topology to achieve small size, high voltage, and isolation. The circuit and battery were sealed in a plastic tube as the Epod. (b) The robot with an Epod assembled onboard. (c) The relation of control, communication, and the actuation of the robot. (d) The data (collected from the pressure sensor) of pressure and voltage relation with various voltages and membrane thickness.

Grahic Jump Location
Fig. 4

Buoyant force increment as a function of voltage, and the effects of initial inner pressure. (a) The relation of buoyant force increment and voltage with various initial inner pressures. (b)–(g) The inflated balloonlike shapes of the DE membrane with no voltage and different initial pressures of 106.0 kPa, 107.0 kPa, 107.5 kPa, 108 kPa, 108.5 kPa, and 109.0 kPa.

Grahic Jump Location
Fig. 5

The experimental results showing the relation of volume and buoyant force with various voltages and membrane thickness, the effect of depth, and their corresponding numerical results from matlab simulation. (a) The relation of volume and voltage. (b) The numerical results of volume–voltage corresponding to the experimental results in (a). (c) The relation of buoyant force and voltage. (d) The numerical results of buoyant force increment–voltage corresponding to the experimental results in (c). (e) The relation of pressure and voltage when the robot is anchored at the certain depth from 25.0 cm to 12.5 cm, respectively. (f) The numerical results corresponding to the experimental results in (e).

Grahic Jump Location
Fig. 6

The experimental data showing the relation of volume, voltage, and the control signal. (a) The relation of the volume and the control signal received by the Epod. (b) The relation of the volume and the voltage generated from the external high voltage source (Trek 610E). The dashed lines link the data points in (a) and (b), calibrating the voltage and the control signal with the identical volume.

Grahic Jump Location
Fig. 7

The flow chart of the control algorithm. When the robot rises above the set point, the measured pressure will be lower than Pon, and the voltage will be turned off. When the robot sinks below the set point, the measured pressure will be higher than Poff, the voltage will be turned off. Pon and Poff can be calculated from the experimental results.

Grahic Jump Location
Fig. 8

The fluctuation of the inner pressures during the operation of control. (b) The fluctuation of inner pressure of the robot is large at the beginning of control. (a) The fluctuation of inner pressure of the robot is reduced and stabilized after control. In the period of the two dashed lines (80.88–87.77 s), there are six cycles of pressure fluctuation.

Grahic Jump Location
Fig. 9

States of the membrane. (a) The reference state of membrane. (b) The prestretched state of membrane. (c) The inflated state of the membrane. (d) The actuated state of the membrane. (e) The schematic of the system with low applied voltage and small volume. (f) The schematic of the system with high applied voltage and large volume.

Grahic Jump Location
Fig. 10

The schematics of the robot during floating and sinking. (a) z is the vertical displacement, which can be calculated from the depths of the robot. (b) When the parameters of the system such as weight, initial pressure, and the thickness of DE membrane are fixed, the control method has a limit of operative depth. Only when the robot locates between the upper and lower limits, can the MCU control and stabilize the robot.

Grahic Jump Location
Fig. 11

The block diagrams of the system. (a) The block diagram of the system without control. (b) The block diagram of the on–off control system. The sampling rate is 20 Hz.




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