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Review

Control Aspects of Shape Memory Alloys in Robotics Applications: A Review over the Last Decade

by
Deivamoney Josephine Selvarani Ruth
1,
Jung-Woo Sohn
2,
Kaliaperumal Dhanalakshmi
3 and
Seung-Bok Choi
4,5,*
1
Robert Bosch Centre for Cyber Physical Systems, Indian Institute of Science, Bengaluru 560012, India
2
Department of Mechanical Design Engineering, Kumoh National Institute of Technology, Daehak-Ro 61, Gumi-si 39177, Korea
3
Department of Instrumentation and Control Engineering, National Institute of Technology Tiruchirappalli, Tiruchirappalli 620015, India
4
Department of Mechanical Engineering, The State University of New York, Korea (SUNY Korea), 119 Songdo Moonhwa-Ro, Yeonsu-Gu, Incheon 21985, Korea
5
Department of Mechanical Engineering, Industrial University of Ho Chi Minh City (IUH), 12 Nguyen Van Bao Street, Go Vap District, Ho Chi Minh City 70000, Vietnam
*
Author to whom correspondence should be addressed.
Sensors 2022, 22(13), 4860; https://doi.org/10.3390/s22134860
Submission received: 10 April 2022 / Revised: 10 June 2022 / Accepted: 15 June 2022 / Published: 27 June 2022

Abstract

:
This paper mainly focuses on various types of robots driven or actuated by shape memory alloy (SMA) element in the last decade which has created the potential functionality of SMA in robotics technology, that is classified and discussed. The wide spectrum of increasing use of SMA in the development of robotic systems is due to the increase in the knowledge of handling its functional characteristics such as large actuating force, shape memory effect, and super-elasticity features. These inherent characteristics of SMA can make robotic systems small, flexible, and soft with multi-functions to exhibit different types of moving mechanisms. This article comprehensively investigates three subsections on soft and flexible robots, driving or activating mechanisms, and artificial muscles. Each section provides an insight into literature arranged in chronological order and each piece of literature will be presented with details on its configuration, control, and application.

1. Introduction

Shape memory alloy (SMA) is a class of smart material wherein it undergoes changes in its length by contracting to nearly 4% and thereby generates a huge amount of resistance force on its thermal actuation. This property of response to thermal stimuli in this alloy makes it smart, unlike the other alloys. There are types of different compositions of SMAs Ni-Ti alloy (Nitinol), Cu–Al–Ni alloy, Cu–Zn–Al alloy, Au–Cd alloy, Ni–Mn –Ga, and Fe based alloys. Only two alloys that have achieved any level of commercial exploitation are Ni-Ti alloys and copper-based alloys. SMA can operate under two different stimuli, one is thermal stimuli wherein, when a pre-stressed SMA wire (detwinned martensite) undergoes a change in temperature to its safe heating temperature (trained temperature) it remembers its parent shape(austenite) along with the stress it will resume back to its product state and this is called the shape memory effect. This type of feature is used for many position/angle tracking control applications. The other one is stress, where the stimulus at the safe heating temperature acts like a spring enabling it to dissipate a huge amount of energy and making it the right choice for use as dampers and absorbers.
In the early stages of SMA literature, the use of proportional derivatives was handled to operate in the systems but later on, it started to be drift to the implementation of nonlinear controllers or hybrid controllers. The control methods implemented on the SMA-based system are mostly implemented using linear controls if the system demands just the actuation and does not need any precision or accuracy. However, there are complex systems, like when using to an instrument in higher-order systems it demands a nonlinear control for performance and efficacy at higher rates. With a wide understanding of the inherent characteristics, there has been immense growth in terms of literature reports and commercial growth [1,2,3,4,5,6,7]. Position control in shape memory alloy (SMA) has been researched only in the last two decades and it has been growing in different areas starting from the design and development of a servo type of operation using the aSMA element in different configurations and by using different biasing elements. The different aspects of using the element to control position and force for robotic and haptic systems are also treated as principal parameters. Some of the features that are to be noted in developing an SMA-based system are to first to first determine the functionality that is going to operate on the system, composition of the element, structural form, and biasing element. Even though SMA is a non-linear element, there are reports in which it has been noted that the output response of the system remains linear in operation. This behavior is undertaken using an active biasing element which is an antagonistic SMA actuator and the way to make it linear is determined by choosing the inverse mechanical element. In other words, the proper selection of biasing elements can be able to maintain the linearity in the response [8].
The main scope of this article is to timely present a state-of-art on mechanical arrangement of the SMA element along with the biasing, which will eventually provide useful guidelines to design more advanced designs for robotic systems. The control strategies that are mostly and frequently employed in SMA-based robots can be classified into two categories: passive control and active control. In the passive control, ON/OFF control and PWM (pulse width modulation) control are dominant in which the actuating force is converted to the stroke or position of the robotic systems. On the other hand, in the active control, PID (proportional-integral-derivative) control and modified PID control logic such as fuzzy-PID control are frequently used for precise position feedback control of small and soft robots.
The manuscript has three sections they are flexible/soft robots, drivers and servo actuators, and artificial muscles. At the start of each section there is a brief definition, followed by the literature papers in chronological order stating the mechanism, movement, control, and the application for which it is built.

2. Flexible and Soft Robots

Soft robotics were developed using bio-inspired compliance to mimic animal or human capabilities Flexible actuators and electronics are employed to design soft robots. Soft robots are made almost entirely of rigid-body architectures out of flexible, soft material, making them suitable for applications in uncertain, dynamic task environments, including safe human-robot interactions with excellent flexibility and adaptability, but their load capacity is limited [9,10]. The flexibility of SMAs allows us to build actuation components in different configurations and shapes (e.g., helical springs, torsion springs, straight wires, cantilever strips, and torsion tubes), which allow them to be adapted to small, micro, and multi-DOF (degree-of-freedom) applications. Their high force-to-weight ratio and small volume (i.e.) SMA displays one of the highest work densities at 10 J cm−3 and can lift more than 100 times its weight—allowing the design of compact and lightweight actuators.
The generic mechanical design for an SMA-based soft robot is an SMA element, which can be a wire or a spring or any other available configuration followed by a biasing element which in soft robotics will be the chassis material by itself or passive, to enable cyclic operation in the SMA element, and the powering mechanism which is usually a joules heating current. In this section, we can discuss the various design, configurations of SMA elements, and control of the SMA actuator in soft robots [4]. The control is mostly on/off as they focus more on the type of motion to generate using SMA elements.
In early 2010, FlexiBot (Flexible Robotic Module) was designed with two degrees of freedom and incorporated four memory alloy (SMA) springs as shown in Figure 1a, to create relative motion between two parallel plates hinged to each other providing 30-degree displacements, which make them more suitable for robotic applications [11]. A four-legged robot [12] was created and actuated by SMA wires along with biasing springs to realize jumping motion as in Figure 1b. A finger-sized wood climbing robot [13] with SMA springs can exhibit the crawl, turn, and climb motion on a tree for search and rescue operations. Peristaltic motion [14] was realized by using the parallel configuration of the SMA element for in-pipe movement as in Figure 1c which was designed to crawl for inspection purposes. A snake robot with three links [15] was designed with a PID-fuzzy controller. A biomimetic fish was actuated by SMA wires [16] in enabling bio-inspired locomotion systems using a deformable structure. The fish is controlled with gains set such that the voltage applied to SMA wires has minimum overshoot and the output of the system has minimal time to achieve stability. A novel climbing mode was developed in millirobots built with SMA wire along with a return spring to execute the climbing potential of the robot [17]. A flexible pectoral fin [18] uses two parallel SMA plates, which can perform a bi-directional bending action, and an elastic membrane made of thin rubber, is adhered to the fin rays to function as a bias element. Flea-inspired catapults with SMA springs were used as actuators that can jump more than 200 times their body length with impulse current stimuli [19]. A biomimetic walking microrobot was designed using 11 ICPF (ionic conducting polymer film) actuators to move and two SMA wire actuators to change motion attitude enabling two kinds of motion attitudes: lying state and standing state [20]. A structure with eight SMA springs was developed to have a helical muscular arrangement to simulate the motion of an octopus muscular hydrostat [21]. A compact external pipe crawler robot [22] was designed by deploying a compliant mechanism and SMA actuation that follows clamp-and-push motion and imitates inchworm motion. A soft robot exhibiting sequential antagonistic motion [23] is achieved in a flexible braided mesh-tube structure using nickel-titanium (NiTi) coil actuators wrapped in a spiral pattern around the circumference that exhibits peristaltic locomotion. Starfish-like robots driven by shape SMA spring actuators [24] were designed to accomplish crawling on flat ground, climbing over viscous soil terrain, free motions in random directions, navigating through a target object, and steering as well as grasping imaginary prey as shown in Figure 1d. A flexible microrobot module (FMM) was actuated by SMA springs [25] and able to provide both translational and rotational displacements. Stiquito hexapod mobile [26] robot was designed using antagonist active Nitinol (NiTi) SMA wire/passive music wire couples to produce moving insect-like legs. The starfish-like soft robot with flexible rays using SMA spring [27] with soft silicone material induces multi-gait movements in various environments. BaTboT, a novel bat-like MAV was studied to increase net body forces by implementing with highly articulated wings actuated by shape memory alloy actuators [28]. Soft caudal fin actuators using SMAs [29] that are fixed along with the soft structure of the caudal fin and bend to a certain mode shape can perform steady swimming and maneuvering. The small one DOF mobile robot is actuated by a pair of SMA springs [30], and the developed mechanism can steer in addition to moving forward on a common plane. Bio-inspired multi-arm underwater robotic swimmers actuated by compliant SMA were modeled and developed by actuating spring elements [31]. A locomotive textile-based robotic system was weaved [32] wherein the fabric is integrated with a woven hybrid SMA-textile actuator based designed system. A soft compliant robot [33] exhibiting an inchworm type locomotion was built and tested. Single-caudal fin propelled robot fish using shape memory alloy wire [34] were developed, as well as unique frog-inspired hind limb robots with SMA spring actuators [35] designed to jump. A biomimetic robotic worm was developed to perform a peristaltic motion by employing nine SMA springs in three sections of the soft robot [36]. A flexible parallel robotic module was actuated by three SMA springs in between a triangular top and base plate connected by a universal joint at its centroid [37]. Shape Memory Alloy actuated controllable suction grippers were proposed and experimented with for a wall climbing hexapod [38]. Soft actuators used to perform actions such as bending, twisting and extending using SMA wires were embedded into actuators to power them [39]. A six-legged robot adapting SMA actuators and a spring antagonistic driving mechanism is able to remain at a specific location in the tree without requiring an external energy supply and can walk and climb in a tilted tree at 30 degrees [40]. For the soft robotic arm driven by shape memory alloy (SMA) coils, with a compression compensation algorithm, a proportional-integral differential controller is used to precisely control the two-dimensional motion with a relatively high accuracy [41].
SMA-based Roll robot actuators [42] can mimic the behavior of rolling animals as designed in Figure 1e. This is a modular closed-chain rolling robot with compliant SMA wires which has the perfect terrain adaptability and maneuverability. An active Tendril-Backbone Robot (ATBR) was built [43] as the manipulator backbone and actuator which utilized the SMA helix. Fuzzy logic control is implemented to control the displacement by currents for underwater robots in [44]. A scheme to drive multiple flexible fins, was presented and verified the feasibility on a flexible robotic fish driven by SMA wire which is inspired by the swimming mode of devil fish, that was able to achieve more stable motion of the fish, and the movement of the whole fish body was more natural and flexible [45]. A 2DOF soft robotic neck was developed and controlled [46] actuated by a flexible SMA based actuator that allows movements of inclination and orientation. PATRICK, a soft robotic brittle star [47] was the first untethered underwater soft robot using the SMA springs to actuate as in Figure 1e and it was built with a high dimensional actuation space, allowing deeper exploration of planning and control principles. SMALLBug, a crawling microrobot that can locomote at actuation frequencies of up to 20 Hz, was designed, fabricated and tested [48]. The robot is driven by an electrically powered 6 mg bending actuator that is composed of a thin SMA wire and a carbon-fiber piece that acts as a loading leaf-spring and four legs capable of generating anisotropic friction. The papers that reported or designed and developed SMA-based soft robots are presented (in chronological order) in the Table 1 which displays the control handle and the parameters that are measured for the particular application.

3. Drivers and Servo Actuations

SMA is an actuator that experiences reduced length enabling a displacement along with force to bring out the work done at that point. Here, the basic element to design is to have an SMA element and a biasing element which would be a passive spring or it can also be active by using SMA elements in an antagonistic configuration to generate a bi-directional movement. The proper design and the understanding of its inherent property changes can enable design of a system with uni-directional or bi-directional linear or rotating movement and any point of application, which proves its use as a driving actuator by substitution in places of traditional classical actuators. An accurate self-sensing method [49] based on the SMA strain to resistance curves for the control of shape memory alloy (SMA) wires biased with passive spring to function as actuated flexures were modeled. An SMA wire actuated gripper was developed [50] to convert the small linear displacement into the angular movement of the gripping fingers to enable open and close functions. A compliant gripper using an SMA coil was fabricated [51] along with a middle flexure joint replicating the behavior of a caterpillar locomotion. A MIniature SwitchAble (MISA) connection system for a stochastic modular robot was designed and implemented [52] which can be switched on and off by controlling four SMA spring actuators. A methodology of actuation to create flow generation in a flexible tube by inducing a variable pressure difference within the tube by external actuation by SMA wires was proposed in [53] shown in Figure 2a. A gripper with soft fingers with 2-DoFs using silicone elastomer rods embedded with shape memory alloy actuators [54], displaying anthropopathic actions was created.
The sensor-less self-sensing circuit for positioning the 1-DOF manipulator arm using antagonistic self-sensing SMA wires as shown in Figure 2b by implementing fuzzy-PID control was proposed and a real-time experiment was performed [55]. An impact drive mechanism (IDM) using SMA wires for positioning applications was found in [56]. A joint with two degrees of freedom (DOF) driven by antagonistic SMA triple wires using a resistance feedback signal in a closed-loop was designed [57]. SMA wires were characterized to function as a High Phase Order Motor (HPOM) using PWM control [58]. A gripper was designed for a robot arm with an anti-slipping control rule to avoid grabbing an unknown object with insufficient force [59]. A conventional PID controller cascaded with a bilinear compensator, known as BPID, is found to be a promising alternative for controlling the position of the SMA actuator [60]. Antagonistic SMA wires were designed in a configuration to the function as a servomechanism [61] for bidirectional control in a super-articulated system. Self-sensing antagonistic SMA wires were used to establish servo mechanism with bi-directional control in a 1-DOF manipulator arm [62]. A compliant differential SMA actuator [63], composed of two antagonistic SMA wires and a mechanical joint, were coupled with a torsion spring. The master-slave system was set up [64] in which the master is equipped with antagonistic SMA wires to perform the actions to control the 2-DOF slave and also to generate force feedback. A smart soft composite (SSC) hinge actuator using SMA wire in a polydimethylsiloxane (PDMS) matrix was embedded with segmented rigid components capable of a pure bending motion concentrated on specific sections of the actuator [65]. A SMA springs actuated gripper [66] is operated to close and open by applying voltage. A tendon-driven bending actuator [67] using smart soft composite (SSC) and SMA, and a sliding mechanism, which mimics flexion of the human hand were designed. A SMA springs actuated gripper is operated to close and open by applying a voltage as in [68]. Active variable stiffness fibers made from shape memory alloy and thermally responsive polymers that can move to a new position and then hold that position without requiring additional power was designed [69].
A SMA-based soft three-fingered curved gripper [70] was designed which is capable of lifting force nearly three times larger than the gripper. A SMA springs-based soft actuator module (SAM) [71] assembling a connected series of four SAM to develop a soft manipulator was designed, which is capable of three-dimensional spatial grasping motion. Finger-wearable haptic devices [72] for multi-DoF cutaneous force feedback driven by four SMA wires for tip-tilt mechanisms and the planar XY spring with four SMA helixes are employed. An artificial finger [73] is a reproduction of the human finger bone and phalangeal structure, actuated by SMA wires. Shape control [74] of compliant, articulated meshes created from shape memory alloy (SMA)-based linear actuators (Active Cells) capable of ~25% linear strain was explored as shown in Figure 2c. A gecko-like gripper [75] that uses series shape memory alloy (SMA) wire for actuation was created. A compact and modular rotary motor using embedded shape memory alloy (SMA) wire was developed as in [76]. The contraction/expansion of the SMA wires is transmitted as rotational motion that enables the motor to generate continuous rotation and provides higher torque with relatively short-length SMA wires. An antagonistically arranged SMA wire-based actuator was fabricated in [77], which can provide angular displacements in both clockwise and counter-clockwise directions with compliance. Robotic grippers with multiple SMA wires in series along with cross-shear coupler to achieve a larger stroke of actuation were designed [78]. A control method for soft robots on predicting the bending force and RBF compensation to obtain accurate position-tracking performance with adjustable stiffness in both open- and closed-loop control systems was presented in [79].
A continuous bidirectional rotary motor driven by NiTi SMA mini springs was designed in [80]. It is noticeable that its torque/volume and torque/mass ratios are prominent when compared to other motors of the same class. An improved method was based on online data-driven control to drive the robot wrist joint driven by SMA [81]. An Adaptive Neuro-Fuzzy Inference System (ANFIS)-based modeling and control of a 1-DOF modular SMA-based rotary actuator with a compliant motion and fast response was proposed in [82]. A control algorithm for the inversion of the Preisach model for a SMA wire spring-biased actuator under time-varying stress produced accurate results and was computationally efficient was formulated in [83]. A foldable nanosized shape memory actuator into 3D configurations presented in [84] can move around. A numerical was developed for reproducing the mechanical response to integration of the time evolution nonlinear equations governing the response of the SMA spring [85]. The control of a soft planar gripper for grasping deformable objects without integrated sensors, in presented in [86]. The soft finger is a closed-loop PID control system to achieve the desired deformation by introducing a camera as a vision sensor, to detect the bending deformation of the soft finger in real-time. The papers that reported or designed and developed SMA-based actuator-based driving mechanisms are presented in Table 2 which displays the control handle and the parameters that are measured for the particular application.
Figure 2. Actuator mechanisms (a) flexible pump [52] (b) bi-directional servo [54] (c) linear actuator–sketch [73].
Figure 2. Actuator mechanisms (a) flexible pump [52] (b) bi-directional servo [54] (c) linear actuator–sketch [73].
Sensors 22 04860 g002

4. Artificial Muscle

SMA actuators, due to their inherent high force to weight ratio feature is an ideal element to replace human muscle, skin, joints, and the skeleton with proper design, configuration, and power units. In this regard, they also found a remarkable place in the development of such a human mimic system. In recent years, our research group has developed a new flexible shape memory alloy actuator that provides more freedom of movement and better integration in wearable robots, especially in soft wearable robots [87]. McKibben developed artificial muscle actuators with shape memory polymers (SMP) [88] to drive robotic joints and these are used in pairs to establish the antagonistic biasing. The wearable supportive device with multiple SMA wires for pulling of the skin (mask) through wires attached to the face as reported in [89].
Biomimetic control of a finger actuated by three antagonistic shape memory alloy (SMA) muscle pairs in [90] was designed, where they are each configured in a dual spring-biased configuration by implementing a fuzzy PWM-PID controller. A modified Hysteresis Functional Link Artificial Neural Network (HFLANN) to control an SMA wire actuator [91] was developed. Artificial skeletal muscle (AM) with functions of actuating, energy-storing, and self-sensing using SMA wires and bias spring as shown in Figure 3 was presented in [92]. A single-joint driving system of a bionic finger using pre-shaped SMA wire as the finger skeleton and the joint was designed [93]. To realize bending and stretching of the proposed finger flexibly, a couple of thermoelectric devices (TEDs) were deployed. Impedance control for antagonistic shape memory alloy (SMA) actuators [94] to operate the lower limb exoskeleton was implemented.
Flexible artificial muscle using coiled shape memory alloy (SMA) wires were created [95] to establish bending motion. The possibility of using a parallel arrangement of SMA wires as an actuator in a robotic hand was showcased in [96]. A high-strain flexible actuator using SMA wire that is wrapped around the two pulleys housed inside the Bowden cable sheath for a wrist exoskeleton was designed [97]. A hybrid actuator combining SMA and a DC motor as described in [98] was designed for prosthetic fingers to improve the rate of grasping force rise in the grasping reflex. A robotic hand using SMA springs was developed [99] and by actuating the SMA springs, the fingers can bend or open. The soft robotic hand designed [100] using shape memory alloy (SMA) and woven type smart soft composite (SSC), used 7 DOF in total. Additionally, 11 woven SSC actuators are integrated with soft material as the united structure. A finger-like manipulator [101] operated using antagonistic NiTi SMA wire was reported. Dynamically artificial flower ornaments using SMA wires [102] to perform, the bending of stems, blooming of petals, spreading of fragrance, and flapping of butterflies were developed. The wearable soft grasping support exoskeleton [103], which has a thin and active fixture, is composed of an SMA wire and an air chamber. A biomimetic control method with a 5 × 3 SMA springs array prototype that has characteristics of artificial muscle [104] was framed. The prosthetic finger uses a linkage mechanism creating an underactuated finger motion and driven by an SMA wire actuator to provide high energy density as presented in [105]. The grasping force model for a two-fingered soft robotic gripper [106] using SMA fiber with variable stiffness was developed. It has been noted that quantitatively the kinematics and the static grasping force of the soft finger can be predicted and the grasping force of the soft finger could be adjusted by changing the Young’s modulus of SMA fiber used in the soft finger. The artificial muscle embedded with SMA improves the effective strain of the SMA wires, and thereby improves the artificial muscle modules significantly [107].
Critical issues due to designing a shape memory alloy (SMA) actuation system for a soft robotic finger with a directly 3D-printed stretchable skin-like multilayered tactile sensor [108] were raised. Underwater experiments were conducted using a nonlinear controller to enable precise fingertip force control using feedback from the compliant tactile sensor. A biomimetic 2-DOF SMA-actuated robotic arm [109] controlled by a wearable sleeve in real-time which can mimic users’ shoulders and elbow flexion extension was designed. A muscle-like SMA coil spring, presented in [110], was embedded in the stretchable active coolant circulation system. Modeling of the hand rehabilitation exoskeleton equipment was tested on the index-finger prototype driven by SMA wire, and the finger muscle force was analyzed based on the Hill model as shown in [111]. Bioinspired composite fingers used SMA wires as self-locking joints to perform long-time and high-load grasping tasks with low power consumption as proposed in [112]. An Ionic glove, wearable over a robotic hand, was developed in [113] which contains sensing, computation, and actuation onboard use shape memory alloy (SMA) actuators integrated into an armband to gently squeeze the user’s arm when pressure is sensed in novel electro-fluid. The types of literature that reported or designed and developed SMA-based actuator-based driving mechanisms are presented in Table 3 which displays the control handle and the parameters that are measured for the particular application.

5. Conclusions

In this review article, three major subclasses of SMA-based robotic systems were investigated and discussed: soft robots designed with flexible actuators, driving mechanisms to bring out both translational and rotational movement, and vital parts (artificial human parts) for developing some elements to replace the human motor system for rehabilitation or exoskeleton module use. The review analysis of each subclass is summarized as follows. (1) The flexible/soft robots mainly featuring the locomotive-legged kind of robots are most commonly designed and developed. For this, the most commonly used control strategies were traditional on/off control or passive control via the open-loop manner. For the open-loop control, the on/off time remains constant and the speed of operation cannot be changed without programming it. Therefore, the types of robots activated by passive control were functioned to jump, crawl, climb, and roll which can be easily operated by SMA wires/springs in combination with proper biasing elements. (2) In the driving mechanism, the SMA element is employed to independently develop as a mechanism to facilitate movement. Thus, it can either be open or closed and uni-direction as in linear translation and bi-directional movement. In this operation, we need a little more precision when compared to the movement of the soft /flexible robots. One of the widely used controllers in the driving mechanism is the fuzzy-PID controller which can be incorporated with the knowledge of the system. (3) In the development of artificial skin/muscle, the controller must be a closed-loop system so that it can handle real-time movement of human motion and mostly this is designed to be a human interface device. For example, both position and speed should be precisely controlled in the SMA-based wrist exoskeleton mechanism using the feedback controllers such as fuzzy tuned controllers. In this field, to develop more sophisticated human-machine interface devices that should guarantee a higher precision in terms of positioning and generating force, more robust feedback control strategies such as a sliding mode controller need to be implemented for SMA actuators.
It is finally concluded that one of the most significant limitations of application of SMA to various types of robotic systems is a relatively slow response to input stimuli such as current/thermal input compared with other smart material actuators such as piezoelectric ceramic. The response of SMA is closely and directly related to the control bandwidth of application robotic systems exhibiting dynamic movement in a wide frequency spectrum. Recently, to resolve this problem, a new type of SMA activated by magnetic field has been developed, but its application for control of robotic systems is burgeoning.

Author Contributions

D.J.S.R. and J.-W.S.: Writing—original draft preparation, investigation, validation; K.D. and S.-B.C.: supervision, conceptualization, writing, reviewing, and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw/processed data required to reproduce these findings cannot be shared at this time as the data also form part of an ongoing study. In the future, however, the raw data required to reproduce these findings will be available from the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest. The authors also declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Figure 1. Flexible robots (a) fish [10] (b) jump-sketch [11] (c) crawl -sketch [13] (d) star fish-sketch [23] (e) roll [41].
Figure 1. Flexible robots (a) fish [10] (b) jump-sketch [11] (c) crawl -sketch [13] (d) star fish-sketch [23] (e) roll [41].
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Figure 3. Artificial skeleton muscle [91].
Figure 3. Artificial skeleton muscle [91].
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Table 1. Control methods of SMA-based flexible and soft robots.
Table 1. Control methods of SMA-based flexible and soft robots.
Control MethodFeatures/Control ParameterApplicationReference
Passive control Heat transfer and constitutive modelFlexiBotAlireza et al., (2010) [11]
Passive controlShort-time pulse activationFour-legged robotThanhtam et al., (2010) [12]
PWM 1Force to stroke OmegabotJ. Koh et al., (2010) [13]
PWMPeristaltic motion mechanism Micro in-pipe Gao et al., (2011) [14]
PID 2-fuzzyPosition control Snake robotKhodayari et al., (2011) [15]
Passive controlContinuous deformable structure Bio-inspired Rossi et al., (2011) [16]
Passive contolStroke control of a coiled SMA MillirobotsKohut et al., (2011) [17]
Passive contolCurvature—phase transformationRobotic pectoral finQin Yan et al., (2012) [18]
Passive controlStiffness to forceFlea inspired catapultNoh et al., (2012) [19]
Passive controlMotion controlBiomimetic microrobotGuo et al., (2012) [20]
Passive controlAgonistic-antagonistic Octopus muscular hydrostat.Follador et al., (2012) [21]
Passive controlCircumferential motion to ring actuators Pipe crawlerSingh et al., (2013) [22]
BB and IL 3Iterative learning controlMesh-wormSeok et al., (2013) [23]
PP 4Path planning control Starfish-like robotMao et al., (2013) [24]
PID and BB 5Positional asymmetric excitationFlexible microrobotAbiri et al., (2013) [25]
Passive controlPeriodic current control Stiquito hexapodFévrier et al., (2013) [26]
Sequential controlKinematic model for motion control to displacement and force Starfish robotShixin et al., (2013) [27]
Passive controlControlling the modulation of currentMicro-aerial vehicleColorado et al., (2014) [28]
PID Bending curvature controlCaudal finCoral et al., (2015) [29]
Passive controlStrain to steer mobilityMobile robotHadi et al., (2015) [30]
Closed loop controllerSpeed and forceRobotic swimmerSfakiotakis et al., (2015) [31]
Passive controlForce coupled with displacementTextile robotsKennedy and Fontecchio (2017) [32]
PWMDifferential frictionInchworm robotPillai et al., (2017) [33]
Passive controlAcceleration and angular velocityRobotic fishLi and Li (2017) [34]
Passive controlPassive force to length of wiresFrog like robotRen et al., (2017) [35]
PWM Control peristaltic motion and the orientationSoft robotAlcaide et al., (2017) [36]
ON/OFF controlLiang dynamic modelFlexible SMA actuatorsRanjith et al., (2018) [37]
Open-loop position controlShear stress controlLegged and non-legged Avadhoot et al., (2018) [38]
Open-loop testingFinite element model Soft gripperSaeed et al., (2019) [39]
Passive controlDeformation and torque for roll yaw directionsLegged robotsIshibashi et al., (2019)[40]
PID controller and CCA 6Bending movementSoft robotsYang et al., (2019) [41]
Passive controlImproved mobility and good terrain adaptabilityRolling robotsNader et al., (2020) [42]
Passive controlBending angles—angular speedContinuous manipulatorSonaike et al., (2020) [43]
Simulation 3D motionBionic Devil FishChen and Liu (2020) [44]
BPID 7Inclination and orientation Soft robotic neckCopaci et al., (2020) [45]
MP and GPA 8Applied current to bending Underwater robotsCruz et al., (2020) [46]
Patterson et al., (2020) [47]
Passive controlHigh-speed thermally-induced transformations SMALLbug Nguyen et al., (2020) [48]
1 Pulse Width Modulation, 2 Proportional-Integral Derivative, 3 Bang Bang and Interative Learning, 4 Path Planning, 5 Bang bang, 6 Compressing Compensating Algorithm, 7 Bilinear Proportional Integral Derivative, 8 Motion Planning and Greedy Planning Algorithm.
Table 2. Control methods of SMA as driving mechanisms.
Table 2. Control methods of SMA as driving mechanisms.
Control MethodFeatures/Control ParameterApplicationReference
Passive control Strain to resistance modelingGripping fingersChao-Chieh et al., (2010) [49]
Passive controlLinear into angular movementThree-fingered gripperKhodayari et al., (2011) [50]
Passive ContolGripping force changes with the length of the flexure jointBio-inspired gripperGwang-Pil et al., (2011) [51]
Passive controlDifferential actuation systemConnection Guoqiang et al., (2012) [52]
Passive controlVariable pressure difference Displacement pumpsKeerthi et al., (2013) [53]
Passive controlGripping force distribution between the finger and the objectSoft robot gripperObaji and Zhang (2013) [54]
Fuzzy-PID controlStrain to differential resistance1-DOF manipulator armJosephine et al., (2013) [55]
PI controlBidirectional strain/displacement to step movementPositioning deviceShinya et al., (2013) [56]
Fuzzy-PID controlResistance feedbackBall joint for end effectorZhenyun et al., (2014) [57]
PWM controlEnhancement of force and controlSMA based motorRossi et al., (2014) [58]
Fuzzy sliding-mode controlAnti-slip control by force sensingRobotic gripperShaw and Lee (2014) [59]
PID controller cascaded with a BPIDPosition controlPosition controlÁlvaro et al., (2015) [60]
Fuzzy-SMCStrain to position controlBall balancing beamSunjai et al., (2015) [61]
(underactuated)
Sliding mode controlStrain to differential resistance1-DOF bidirectional servo actuationJosephine et al., (2015) [62]
PI and saturated PIStiffness and complianceServomechanismZhao et al., (2015) [63]
PD controlElectrical resistance and force feedback (haptics)Master-slave systemsJosephine et al., (2016) [64]
Passive controlPulling and graspingThree-fingered gripperWei et al., (2016) [65]
Passive controlBending and load holdingRobotic handHyung et al., (2016) [66]
PWMClose and open GripperRad et al., (2016) [67]
Passive controlActuation and variable stiffnessRobotic skinYuen et al., (2016) [68]
Passive controlThermoconstitutive model
deformation of the actuator
Curved gripperHugo et al., (2017) [69]
Higher-order SMCDifferential electrical resistance1-DOF manipulator armJosephine et al., (2017) [70]
PWMSMA resistance, self-feedback Soft manipulatorZhang et al., (2017) [71]
Passive controlTouch/pressure—shearing forceHaptic deviceLim et al., (2017) [72]
Passive controlExtension and flexion forceProsthetic handVan der et al., (2017)[73]
PD controlShape control based linear actuators -Active CellsMACRONawroj et al., (2017) [74]
Passive controlAdhesive pressure controlGecko inspired gripperMehdi et al., (2018) [75]
Open-loop testingContinuous and bidirectional rotationWearable rehabilitation Hwang et al., (2018) [76]
PID controlAngular displacements with complianceSoft bio-inspired robotic systemsYoungshik et al., (2019) [77]
Open-loop testingTheoretical model of grasping force for different capturing targets.Robotic gripperYifan et al., (2019) [78]
Radial basis function (RBF) + SMCTwo different position controlsSoft robotJunfeng (2019) [79]
Open-loop controlNumerical and experimental responses of angular displacement, force, and torqueServo drive (motor)José et al., (2020) [80]
Data driven controlDisplacement controlRehabilitation medical devicesZhang et al., (2020) [81]
ANFISClosed-chain serial mechanismBio-inspired and soft roboticsMansour et al., (2020) [82]
Open-loop controlActive cooling system for efficient responseWearable roboticsJoey et al., (2020) [83]
Open-loop controlCurvation variationFoldable robotCordelia (2021) [84]
Backward Euler time integration algorithm and the prediction-correction techniqueEuler time integration algorithm and the prediction-correction techniqueSMA actuatorEsposito et al., (2021) [85]
PID controlGripping forceSoft gripperWei et al., (2021) [86]
Table 3. Control methods of SMA as artificial muscle and finger.
Table 3. Control methods of SMA as artificial muscle and finger.
Control MethodFeatures/Control ParameterApplicationReference
Passive controlTension to length relationshipRobotic arm jointsKazuto et al., (2010) [88]
PID controllerDisplacement/Strain Robot mask systemJayatilake et al., (2010) [89]
Fuzzy PWM-PID Bi-directional motionAnthropomorphic artificial fingerJunghyuk et al., (2011) [90]
Predictive control HFLANNLinkagesNguyen et al., (2012) [91]
Fuzzy tuned PID controllerForce–velocity and force–length relationships1 DOF robotic ankle-footJianjun et al., (2012) [92]
PI controller Strain to bending angle Bionic fingerSun et al., (2012) [93]
PID controllerImpedence controlExoskeletonsAraujo et al., (2012) [94]
Passive controlBending angleFlexible Artificial Muscle Actuator Hironari (2013) [95]
adaptive PIDHysteresis-prone phase transitionRobotic handGerrit et al., (2015) [96]
Hammerstein-Wiener modeled PID gainsPosition and speed controlWrist exoskeletonVilloslada et al., (2015) [97]
Passive controlImproving reflex speed by controlling voltageProsthetic fingerFei Gao et al., (2015) [98]
Passive controlStrain to bending angle Prosthetic fingerAhmadi et al., (2015) [99]
Passive controlBending curvature controlBio-mimetic soft hand.Kim et al., (2015) [100]
Passive controlThermal setting techniqueRobotic fingerDilibal et al., (2015) [101]
PWMDeflection controlArtificial flowersPan et al., (2015) [102]
Passive controlHolding/grasping forceGrasping support exoskeletonHasegawa and T. Suzuki (2015) [103]
Programmable logic controllerDisplacement and ForceArtificial muscleYing et al., (2015) [104]
Passive controlUnderactuated finger motionRobotic fingerLee et al., (2016) [105]
CharacterizationCosserat theory-based grasping force modelSoft robotic gripperYin et al., (2018) [106]
Open-loop tension testsStrain and weaving angle correlationArtificial muscle modulesKong et al., (2018) [107]
PID controlPrecise fingertip force control using feedback from the compliant tactile sensorUnderwater gripperMaohua et al., (2020) [108]
PID controller Joint angular positionRehabilitation, haptics, and, surgical roboticsGolgouneh et al., (2020) [109]
Open-loop controlActive cooling system for efficient responseWearable roboticsJeong et al., (2020) [110]
PWMCoupling dynamic model for modeling and analyze ExoskeletonWang et al., (2020) [111]
Open-loop controlSelf-locking jointsAssisting UAV for perching and grasping bio-inspired fingerHu et al., (2021) [112]
Open-loop controlIntuitive graspingProsthetic handSimons et al., (2021) [113]
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Ruth, D.J.S.; Sohn, J.-W.; Dhanalakshmi, K.; Choi, S.-B. Control Aspects of Shape Memory Alloys in Robotics Applications: A Review over the Last Decade. Sensors 2022, 22, 4860. https://doi.org/10.3390/s22134860

AMA Style

Ruth DJS, Sohn J-W, Dhanalakshmi K, Choi S-B. Control Aspects of Shape Memory Alloys in Robotics Applications: A Review over the Last Decade. Sensors. 2022; 22(13):4860. https://doi.org/10.3390/s22134860

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Ruth, Deivamoney Josephine Selvarani, Jung-Woo Sohn, Kaliaperumal Dhanalakshmi, and Seung-Bok Choi. 2022. "Control Aspects of Shape Memory Alloys in Robotics Applications: A Review over the Last Decade" Sensors 22, no. 13: 4860. https://doi.org/10.3390/s22134860

APA Style

Ruth, D. J. S., Sohn, J. -W., Dhanalakshmi, K., & Choi, S. -B. (2022). Control Aspects of Shape Memory Alloys in Robotics Applications: A Review over the Last Decade. Sensors, 22(13), 4860. https://doi.org/10.3390/s22134860

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