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. 2020 Nov 1:315:112221.
doi: 10.1016/j.sna.2020.112221. Epub 2020 Aug 10.

Compliant Underwater Manipulator with Integrated Tactile Sensor for Nonlinear Force Feedback Control of an SMA Actuation System

Maohua Lin  1 , Morteza Vatani  2 , Jae-Won Choi  2 , Savas Dilibal  3 , Erik D Engeberg  1
Affiliations

Compliant Underwater Manipulator with Integrated Tactile Sensor for Nonlinear Force Feedback Control of an SMA Actuation System

Maohua Lin et al. Sens Actuators A Phys. .

Abstract

Design, sensing, and control of underwater gripping systems remain challenges for soft robotic manipulators. Our study investigates these critical issues by designing a shape memory alloy (SMA) actuation system for a soft robotic finger with a directly 3D-printed stretchable skin-like tactile sensor. SMA actuators were thermomechanically trained to assume a curved finger-like shape when Joule heated, and the flexible multi-layered tactile sensor was directly 3D-printed onto the surface of the fingertip. A nonlinear controller was developed to enable precise fingertip force control using feedback from the compliant tactile sensor. Underwater experiments were conducted using closed-loop force feedback from the directly 3D-printed tactile sensor with the SMA actuators, showing satisfactory force tracking ability. Furthermore, a 3D finite element model was developed to more deeply understand the shape memory thermal-fluidic-structural multi-physics simulation of the manipulator underwater. An application for human control via electromyogram (EMG) signals also demonstrated an intuitive way for a person to operate the submerged robotic finger. Together, these results suggested that the soft robotic finger could be used to carefully manipulate fragile objects underwater.

Keywords: Soft robot; electromyogram; multi-physics simulation; shape memory alloy; tactile sensor.

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Conflict of interest statement

Conflict of Interest 1. This manuscript is the authors’ original work and has not been published nor has it been submitted simultaneously elsewhere. 2. That all authors have checked the manuscript and have agreed to the submission.

Figures

Fig.1.
Fig.1.
Antagonistic actuation concept using two thermomechanically trained SMA plates. Integrated tactile sensing enables force control. The color of the actuators indicates the temperature during different times in the actuation cycle, where Joule heating is used to alternately flex and extend the actuators to drive the finger.
Fig. 2.
Fig. 2.
a. (i) Fabrication of the first mold to create the inner part of the finger: exploded and assembled view for SMA, (ii) Inner finger assembly after molding, (iii) Thermal/electrical insulator tubes for the SMA plates. b. 3D printing a tactile sensor on the inner molded part. c. Placing the inner mold part in the outer mold. d. (i) Assembled underwater manipulator schematic, (ii) The final assembled manipulator compared with human finger, (iii) Top view of each ‘U’ shaped SMA actuator that was cut from a 1mm thick plate using an electric discharge machine, (iv) Top view of tactile sensor’s upper and lower layers (unit: mm).
Fig. 3.
Fig. 3.
Nonlinear force controller for the finger using feedback from the directly printed tactile sensor. This was evaluated with three different kinds of inputs: steps, sinusoids, and EMG signals.
Fig. 4.
Fig. 4.
Illustrative data of the step response of the finger. a. The 7.78 N amplitude input was accurately tracked. b. The error of the system increased sharply at the rising edge of each step input but was rapidly driven to zero. c. The manifold (S) of the nonlinear force controller saturated at the maximum and minimum permissible levels to rapidly minimize the force tracking error. d. Current flowed through the flexor SMA actuator (IF) to increase and maintain the applied fingertip force whereas current flowed through the extensor actuator (IE) to decrease the fingertip force.
Fig. 5.
Fig. 5.
a. Step responses of the SMA actuated finger with force feedback from the directly 3D-printed compliant tactile sensor. Force tracking and steady state error were satisfactory for all amplitudes. b. The slope of the increasing and decreasing forces were nearly identical for all step amplitudes, as demonstrated by the superposition of the data.
Fig.6.
Fig.6.
a. Illustrative sinusoidal tracking data for the high and low amplitudes with five different frequencies. b. Means and standard deviations of the sinusoidal tracking experiments with the high (FH) and low (FL) amplitude desired force inputs of 6 N and 3 N, respectively.
Fig. 7.
Fig. 7.
EMG input to control the fingertip force. a. When the forearm muscles were relaxed, the desired force was nearly zero and the finger was not contacting the pencil. b. As the wrist flexor muscle contracted, the desired force increased and the SMA finger responded by matching the desired force on each cycle of flexion and extension. c. The force tracking responses of the SMA actuated finger consistently tracked the desired force specified by the EMG signals. d. The force tracking error was always less than 1N and the mean absolute error was 0.32N.
Fig. 8.
Fig. 8.
The experimental and simulated motions of the flexor actuator showed that Joule heating the SMA caused the finger to flex. a (i) The actual SMA shape. (ii) The simulated displacement field at the initial stage. b (i) The actual SMA shape. (ii) The simulated displacement field at 1s. c (i) The actual SMA shape. (ii) The simulated displacement field at the last stage.
Fig. 9.
Fig. 9.
Thermal-fluidic-structural system of an underwater manipulator. a. The fluid field of the environmental water in which larger arrows indicate higher velocity. The pressure of the fluid on the finger surface showed an increasing trend with increasing input force amplitude and frequency. b. The velocity field of the SMA inside the water. c. The thermal field of SMA in which red means a higher temperature, blue means a lower temperature. d. The displacement field of the sensor in which red means a higher displacement, blue means a lower displacement. All conditions a-d were under (i) 0.45 rad/s with low (FL) amplitude desired force input of 3 N (ii) 0.45 rad/s with high (FH) amplitude desired force input of 6 N (iii) 0.75 rad/s with high (FH) amplitude desired force input of 6 N.
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