A High-Deformation Electric Soft Robotic Gripper via Handed Shearing Auxetics by Lillian Tiffany Chin B.S., Massachusetts Institute of Technology (2017) Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Master of Science at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 2019 ○c Massachusetts Institute of Technology 2019. All rights reserved.
Author...... Department of Electrical Engineering and Computer Science May 16, 2019
Certified by...... Daniela Rus Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science, CSAIL Director Thesis Supervisor
Accepted by ...... Leslie A. Kolodziejski Professor of Electrical Engineering and Computer Science Chair, Department Committee on Graduate Students 2 A High-Deformation Electric Soft Robotic Gripper via Handed Shearing Auxetics by Lillian Tiffany Chin
Submitted to the Department of Electrical Engineering and Computer Science on May 16, 2019, in partial fulfillment of the requirements for the degree of Master of Science
Abstract This thesis describes the development of a new class of electrically-driven soft robotic actuators built from handed shearing auxetics (HSAs). Soft robots – robots made out of more compliant materials such as rubber and sili- cone – are significantly more robust and safer than their rigid-bodied counterparts due to their intrinsic compliance. However, existing soft robots are mostly fluid-driven, causing them to be significantly more energy inefficient, susceptible to puncture and limited in controllability. To address these issues, we use HSAs to create compliant actuators without the inherent issues of pneumatic actuation. Through analysis of planar symmetry groups, we add chirality to shearing auxetic patterns, creating materials that expand with a handed bias when pulled in tension. This new metamaterial design enables us to create new structures that have a strong coupling between twisting and extension, letting us use traditional electric-based motors to get linear motion. In this thesis, we explain the theory behind this new class of auxetics, demonstrate how HSAs can be coupled to form compliant linear actuators, and characterize the actuators’ performance in a variety of applications. This work culminates in an electrically driven soft robotic gripper which is significantly smaller, more energy efficient and more puncture resistant than existing pneumatic soft robotic grippers.
Thesis Supervisor: Daniela Rus Title: Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Com- puter Science, CSAIL Director
3 4 Acknowledgments
Although the mythos of the lone hero scientist is an enduring one, research is a social endeavor. These acknowledgments are inadequate for both listing everyone who helped me as well as the extent of their help. My advisor, Daniela Rus, has been invaluable not only as an expert in technical in- novation and narrative building, but also as a role model as a female leader in STEM. Her drive to keep the gradient in both the technical and community aspects helped create a familial atmosphere in the lab. Every day, I was blessed with Ryan Truby and John Romanishin’s technical expertise, Andy Spielberg and Brandon Araki’s dry wit, and Mieke Moran’s kind logistical wizardry. A particularly special thanks goes to Jeffrey Lipton, for mentoring me as a SuperUROP onwards. I really appreciated our rapid-fire discussions from technical ideas to baby updates. The lab atmosphere, of course, echoed the support I received outside of lab. My parents, Lih-Shen Chin and Lian Li, have been there for me ever since I could crawl into their lab and bother their graduate students. I would not be here without their unwavering support of my scientific interests. The entire _house clan – Ava Chen, Wesley Lau, Kris Kim, and Jonah Ko – really helped me survive the day-to-day trials and tribulations of graduate school, whether it was the personal attacks, home- cooked dinners, or guinea pig feedings. Rachel Holladay and the rest of chilly-lin@ / spicy-ren@ provided the clutch save by volunteering to turn this thesis in. Finally, I’d like to thank James Rowan for the late-night phone calls, the philo- sophical musings, and the past five years of commitment. This work was done in the Distributed Robotics Laboratory at MIT with sup- port from The Boeing Company, Amazon, JD, the Toyota Research Institute (TRI), the NASA Space Technology Research Grant NNX13AL38H, and the National Sci- ence Foundation – grant numbers EFRI-1240383, IIS-1226883, CCF-1138967, and #1830901. I was personally supported under the National Science Foundation Grad- uate Research Fellowship grant #1122374, the Paul & Daisy Soros Fellowship for New Americans, and the Fannie and John Hertz Foundation.
5 6 Contents
1 Introduction 15 1.1 Thesis Organization ...... 18
2 Background 21 2.1 Soft Robotics ...... 21 2.1.1 Actuators ...... 21 2.1.2 Grippers ...... 24 2.2 Auxetics ...... 24 2.2.1 Auxetics in Robotics ...... 25 2.2.2 Handed Shearing Auxetics ...... 25
3 Actuator Design 29 3.1 Paired Chiralities ...... 29 3.2 Materials, Methods and Fabrication ...... 31 3.2.1 Material Selection ...... 31 3.2.2 Fabrication ...... 32 3.2.3 System Integration ...... 33 3.3 Actuator Applications ...... 34
4 Gripper Design 37 4.1 Constraint Layers ...... 37 4.2 Fabrication and System Integration ...... 38
7 5 Experimental Results and Characterization 41 5.1 Characterization of Actuator ...... 41 5.2 Characterization of Gripper ...... 44 5.3 Comparison to Pneumatic Soft Gripper ...... 46 5.3.1 Mechanical Performance ...... 47 5.3.2 Grasping Performance ...... 51 5.3.3 Power Efficiency ...... 53
6 Discussion 55 6.1 Lessons Learned ...... 56 6.2 Future Work ...... 57
A Code 59
8 List of Figures
1-1 The use of (A) handed shearing auxetics allow us to create a novel class of compliant electric actuators, with applications as diverse as (B) linear actuators, (C) a four degree-of-freedom robotic platform, and (D) a robotic gripper...... 17
2-1 Overview examples of the auxetic trajectories for conventional auxet- ics, shear auxetics and handed shearing auxetics. As 휃 varies (arc in blue), the auxetic pattern expands and contracts, with maximum ex-
pansion occuring at 휃푚푎푥. While the top two auxetic classes have mirror
symmetry at 휃푚푎푥, the bottom two do not, allowing those classes to maintain a single chirality throughout their trajectory. Figure origi- nally appeared in [30] ...... 27
3-1 Schematic of how pairing handed shearing auxetics of different hand- edness create an actuator. If we constrain the pair on the top and counterrotate the cylinders against each other, each tube will expand, leading to bulk extension...... 30
3-2 (A) Demonstration of a linear actuator made from handed shearing auxetics. Through a series of gears driven by a conventional servo motor, the two cylinders counterrotate against each other, creating extension. (B) This linear actuator is also quite compliant, allowing it to benefit from greater environmental interaction...... 34
9 3-3 Demonstration of the full four degrees of freedom of the robotic plat- form. By composing two left-handed and two right-handed shearing auxetics, the platform can rotate in all directions as well as extend, depending on which cylinders are actuated. Figure originally appeared in [30] ...... 35 3-4 When the handed shearing auxetic (HSA) cylinders are overactuated, helical instability can occur where the cylinders twist in on themselves. This typically happens when either (A) the HSAs approach their state of maximal expansion or (B) when an external constraint adds extra force to the system...... 36
4-1 Demonstration of how (A) adding a constraint layer to the base handed shearing auxetic pattern causes out of plane bending fingers. The red circles show the diagonal constraint while the blue circles show the end cap top constraint. (B) Shots from head-on and (C) in profile reveal how the constraint layer goes from a diagonal wrap to a straight internal radius of the bending circle...... 39 4-2 Overview of the gripper design. Each finger is made out of a pair of handed shearing auxetic cylinders that can bend out of plane. These actuators are driven by a motor to bend. A silicone glove, palm, and neoprene foam add more points of contact and friction. Figure origi- nally appeared in [9]...... 40
5-1 Cyclic tensile loading of a handed shearing auxetic cylinder when ro- tation is allowed (red curve) and when the cylinder is held in place (blue curve). When rotation is allowed, significantly lower stiffness is reported (193 ± 0.3 N/m vs. 285 ± 0.7 N/m), revealing how the HSA naturally couples twisting with extension...... 42 5-2 Motion capture results of the movement of a handed searing auxetic actuator pair with an added constraint layer to enable out-of-plane bending. Figure originally appeared in [11] ...... 45
10 5-3 (A) Overview of pneumatic and handed shearing auxetic-based grip- pers, alongside their driving hardware. Closeups of the (B) pneumatic hand and (C) handed shearing auxetic grippers reveal their different morphologies and grapsing behavior. Figure originally appeared in [9]. 46 5-4 Demonstration of puncture resistance of a handed shearing auxetic gripper. (A) Normal operation is indistinguishable from (B) the grip- per after repeated laceration damage or (C) repeated puncture damage. Figure originally appeared in [10] ...... 50 5-5 Array of objects used in grasp testing. (A) Objects successfully grasped by both grippers. (B) Objects only grasped by the handed shearing auxetic based gripper. (C) Objects only grasped by the pneumatic gripper. (D) Objects that were not able to be grasped by either gripper. Figure originally appeared in [9] ...... 52
11 12 List of Tables
5.1 Mechanical Properties of Handed Shearing Auxetic Actuators . . . . 43 5.2 Comparison of Pneumatic vs. Handed Shear Auxetic Grippers . . . . 48
13 14 Chapter 1
Introduction
Soft robotic manipulators offer great promise for increased human-robot interaction. Traditional rigid-bodied grippers often have trouble in real-world situations due to the uncertainty inherent to everyday operation. Accurate grasping for a rigid ma- nipulator requires precise knowledge of a scene’s layout, the object’s location and geometry in order to avoid obstacles and path plan correctly. This data is infeasible to collect for typical applications such as elder care or home assistance, which are often dynamic with a large array of potential objects and interactions. By contrast, soft robots’ compliance allows them to perform better while simultaneously reducing the amount of computation required. By allowing its lower stiffness to compensate for environmental uncertainty, a compliant gripper follows rather than fights envi- ronmental constraints. Soft robots’ continuously deformable bodies allow them to conform around objects, enabling them to grasp a greater diversity of objects with- out needing an immense amount of prior information [49, 19]. With their increased safeness, robustness and improved grasping performance, soft robotic manipulators have the potential to allow robotics to finally make the jump from the structured environment of the factory or lab to the unstructured realm of the kitchen or hospice. Currently, most soft robotics are driven by fludic actuators, such as pneumatics [20, 34], hydraulics [22, 40], or through vacuum [28, 48]. These fluid-based actuators are popular due to their ease of fabrication, fast response time and high strength-to- weight ratios [44]. However, in order to translate electric power to fluid movement, all
15 of these actuators require significant driving infrastructure in the form of compressors, pumps, and valves – adding physical bulk and power inefficiencies to an otherwise simple system [26]. These actuators are also all susceptible to puncture, as a single hole in the fluid line will render the system useless. Even without mechanical damage, the high forces involved in fluidic actuation can still cause the internal walls totear and burst [53]. Although other non-fluidic approaches to soft robotic actuation exist, such as cable-driven [37], shape memory alloy [57], and electroactive polymer based systems [23], these schemes often require either exotic materials or complex driving hardware, limiting their utility and implementation. To fully deliver on the potential of soft manipulators, there is a clear need to create a simple, electrically-driven, puncture-resistant soft robotic gripper.
To address these issues, we propose a new class of compliant electric actuators through handed shearing auxetics (HSAs). HSAs are a mechanical metamaterial which strongly couple a rotary twist with linear extension based on their inherent geometric pattern [30]. This enables the torque from normal electric motors to create a diverse range of motion across any material. Both linear extension and bending motion can be obtained by modifying the base pattern of the HSAs – similar to the performance of existing fluidic actuators, but without the associated power inefficien- cies or susceptibility to puncture.
In this thesis, we discuss the theory behind HSA-based actuators, explaining how pairing two cylinders of opposite chirality enables compliant sustained motion. We then use this concept to create a whole series of robotic actuators: from a linear actuator that can extend by 60% of its intial length, to a four degree-of-freedom (DOF) robotic platform that can pitch and roll by 100∘ and yaw by 280∘. This work culminates in directly contrasting a soft robotic gripper against a state of the art pneumatically driven gripper [18]. The HSA gripper performs similarly to the pneumatic gripper in terms of number of objects grasped, but is significantly easier to construct, more puncture resistant, and uses smaller, more energy efficient driving hardware. The characterization and experiments of the HSA actuators demonstrate the viability and potential of HSAs for soft robotic actuation.
16 Figure 1-1: The use of (A) handed shearing auxetics allow us to create a novel class of compliant electric actuators, with applications as diverse as (B) linear actuators, (C) a four degree-of-freedom robotic platform, and (D) a robotic gripper.
17 Specifically, this thesis makes the following contributions to robotics research:
∙ Design a new class of compliant electric actuators based on counterrotating HSA cylinders
∙ Demonstrate how constraining the base HSA pattern can produce bending ac- tuators
∙ Showcase the utility of this approach by creating linear actuators, a four degree- of-freedom robotic platform and a soft gripper
∙ Characterize the mechanical, electrical and grasping performance of our actua- tors and grippers, contrasting with existing fluidic soft robotic systems
1.1 Thesis Organization
This thesis is based on the following academic papers co-written by the thesis author. Bolded titles indicate primary authorship.
1. "Handedness in shearing auxetics creates rigid and compliant structures" [30] – provides theory behind HSAs featured in Ch. 2
2. "Compliant Electric Actuators Based on Handed Shearing Auxetics" [9] – basis for Ch. 3 - 5
3. "A Simple Electric Soft Robotic Gripper with High-Deformation Hap- tic Feedback" [11] – provides some characterization experiments for Ch. 5
4. "Automated Recycling Separation Enabled by Soft Robotic Material Classification" [10] – provides some characterization experiments for Ch. 5
Chapter 2 provides an overview of related work. We present a summary of the current state of soft robotic actuators and grippers, a description of the use of auxetics in robotics, and a brief discussion of the theory behind HSAs.
18 Chapter 3 describes how we adapt HSAs to be used as compliant linear actuators, demonstrating our findings by fabricating a linear actuator and a four degree-of- freedom robotic platform. Chapter 4 explains how a compliant robotic gripper can be created by modifying the base HSA design to enable out-of-plane bending. Chapter 5 characterizes the actuators and gripper designed in Ch. 3 and 4 in terms of mechanical properties, range of motion, and stiffness. The HSA-based grip- per is then compared to a state-of-the-art pneumatic soft gripper in terms of grasp performance, power consumption, and ease of fabrication. Finally, Chapter 6 concludes with a discussion of the HSA-based gripper and potential future work.
19 20 Chapter 2
Background
2.1 Soft Robotics
Soft robotics is an emerging field which seeks to use intrinsically compliant robotic bodies to reduce computational requirements and adapt to unknown or unpredictable applications [49]. The idea of using compliance to better tolerate environmental uncertainties is not a new one; in particular, series elastic actuators – which place a spring element in series with a traditional motor and gear train – have been demonstrated to better absorb shocks and be easier to control [45, 42]. However, rather than adding compli- ance later in the design process through the addition of elastic elements or new control schemes [31], soft robotics is interested in compliance from the materials level. This focus on materials allows us to design with a greater range of stiffnesses and com- pliances, allowing us to make robots which can continuously deform without being limited to pre-inscribed rigid joints [47].
2.1.1 Actuators
Having actuators that can match the high deformations and compliance of a soft robot body can be difficult. The actuation scheme must allow whole body deforma- tion without needlessly restricting that same motion. Current soft robotic actuators
21 generally falls under three categories: (1) fluidic actuation, (2) tendon / cable-driven systems, (3) material-specific actuation. Fluid-driven soft robots are by far the most common actuation scheme. Whether called "fluidic elastomer actuator", "pneumatic artificial muscle", or "McKibben ac- tuators", these systems are composed of fluid-filled embedded chambers within a flexible material. Adding fluid into these chambers changes the pressure within the system and causes global expansion / contraction. Stiffer areas of the robot will de- form less than softer areas, so kinematic behavior can be designed by constraining some areas over others [43]. Most fluidic actuators follow the Pneunet design introduced in [20], which uses pneumatic actuation within a bulk silicone system constrained by strain-limiting lay- ers. The simple bending version of this design has been used to make effective and resilient soft manipulators and walkers [40, 56]. Endless variations of this design exist, including adding constraints via fiber reinforcement or using hydraulics as the inter- nal fluid [14, 12, 33]. This pneunet design is so popular because they are relatively simple to fabricate designs. The molding and casting process is easy to modify to create the most appropriate system for the application [34]. However, all of these actuation schemes suffer from two fundamental issues. First, fluidic systems must convert electric signals to fluid movement, regardless of whether powered by air, water or vacuum [47]. An external pump or compressor is needed to pressurize the working fluid, creating extra physical bulk and energy inefficiency that traditional rigid robots don’t have. Attempts to improve this include making more efficient converters or avoiding the use of compressors by relying on thermal expansion of fluids instead [35, 38, 47]. These solutions, however, deflect the key issueofthe inherent inefficiency of moving fluids based on electrical signals. Second, all fluidic-driven robots are susceptible to puncture. The interconnected nature of their bladders mean that a single point of failure is distributed across the other fluid chambers. Solutions to this problem have focused on mitigating the effect of the failure, either by embedding fibers to close the hole upon object removal or enabling self-healing through the polymer chemistry of the bulk material [53, 21].
22 These methods require significant time to heal and only work for specific material types and geometries.
Cable-driven systems are the second most common actuation scheme. Cables are embedded within a soft body, typically guided through pulley systems or sheaths to reduce friction. Changing the lengths of these tendons allow different sections to move. Cable-driven systems have been used to create compliant biomimetic systems, due to the similarity of these systems to actual biological muscle and tendon mod- els [32]. Robotic octopus tentacles and worms have used cables to achieve complex motion [37, 5]. However, in order to maintain the necessary tension for successful force transmission, a significant amount of infrastructure is necessary to ensure a taut line. This single transmission line also leads to the same issue of cascading failure as the pneumatic systems; a single cut could render the entire system useless.
Material-specific actuation is a broad catch-all category, intended to capture ac- tuation schemes that rely on specific materials rather than general actuation schemes that can be applied on any existing body. Some examples of material-specific actua- tion includes shape memory alloys (SMAs), which can be deformed and restore their shape upon the application of heat, and electroactive polymers (EAPs) / dielectric elastomeric actuators (DEAs), which change size and shape when placed under an electric field [24, 2]. Although significant research has been done on DEAs andEAPs, these materials are overall still in development to use practically in soft robotics, es- pecially given the high voltage that most require to function [58, 23]. SMAs have been used more successfully in a wide range of robots, as their temperature-based mechanism and low profile makes them an easy actuation option [29]. However, the large energy consumption needed to heat the wire and long cooldown time make them unable to perform quickly and efficiently. Overall, relying on specific exotic materials for actuation limits potential applications and designs.
None of these current actuation schemes can quite match the versatility and ef- ficiency of conventional motor-driven transmissions used in rigid robots. Thereisa clear need for an actuation scheme that can leverage the optimized design of motors with the flexibility demanded by soft robots.
23 2.1.2 Grippers
Soft robots’ compliance makes them a good fit for manipulation tasks. Soft grippers can grasp a wide range of objects without using complex controls as they are able to conform around grasped objects without fear of crushing them [60]. Most grippers directly follow from the actuation schemes listed above. A bending actuator can be directly used as a finger for a soft gripper. For example, the Pneunet paper directly demonstrated a starfish-like gripper that could pick up an egg [20], while [12] extended this concept to create a human-like gripper with biomimetic behaviors. Similar analogues exist for the other types of actuation schemes as well. [41] is composed of rigid links connected with elastomeric flexure joints and driven by cables, granting compliance and robustness to a traditionally rigid articulated system. Thin film gripper examples have also been successfully created with fiber-reinforced DEAs, despite limitations in geometry [54]. Some of the more creative grippers involve a combination of the actuation tech- niques to enable complex dynamic motion. [37] combines SMA coils to provide con- tractile motion with tendon-driven systems for longitudinal motion to create con- tinuum motion. Meanwhile, [13] drives soft segments with cables while using shape memory polymers to control the stiffness of specific joints Other gripers are not easily generalizable from their actuation technique, instead relying on other mechanisms to enclose and grasp an object. One such example is the granular jamming gripper, which uses a vacuum to force small particles to conform and jam around an object [6]. Exploiting these passive properties in conjunction with the more active techniques listed above may ensure even greater conformation [55, 19].
2.2 Auxetics
Auxetic materials are those with a negative Poisson’s ratio; when pulled under ten- sion, these materials will expand perpendicularly rather than contract as typically expected [16]. Although this property occurs naturally in some materials at the chemical bond level [59, 3], most auxetic materials are made through the geomet-
24 ric design of a metamaterial. By repeating a regular pattern of struts and joints, any base material can be made auxetic at any scale [25, 4]. This material and scale independence opens up a wide range of design possibilities for auxetic applications.
2.2.1 Auxetics in Robotics
Although research in auxetics has been a rich area of material science research since the 1970s, the application of auxetics for robotics has remained relatively limited. Many have highlighted that auxetics are a potentially interesting material for soft robotic applications [39, 50]; however, most robotic uses of auxetics tend to just use these materials as a passive constraint system. [51] used auxetics as a sleeve for a nor- mal soft pneumatic actuator in order to cause different kinematic behavior, while [36] sandwiched a linear actuator between an auxetic and a conventional material to cre- ate jamming inchworm-like crawling up a tube. [8] expands on this peristaltic motion, by combining an auxetic with a constraint layer to force lateral slithering motion for slithering locomotion. These applications do not take full advantage of auxetics’ abil- ity to transduce forces in different directions or its properties as a metamaterial. [27] comes closer to this ideal, by controlling the Poisson ratio across the system by selec- tively filling / emptying "mechanical pixels" along its surface. However, there isno clear way to scale this technique to larger scales. Part of the difficulty in using auxetic materials for real-world applications isbeing able to cause useful movement. Although significant work has been done to create new forms of auxetic metamaterials, most require complex fabrication and actuation schemes [1, 52]. In addition, finding materials that are able to sustain the large deformations needed for the flexure-based metamaterial designs has proven somewhat difficult [46].
2.2.2 Handed Shearing Auxetics
This thesis builds significantly off of the class of auxetics developed in [30]: handed shearing auxetics (HSAs). HSAs put a twist on the concept of traditional auxetics’
25 isotropic uniform expansion by forcing chiral anisotropic behavior instead.
HSAs approach auxetics in the context of "angular trajectories" as outlined in [16, 15], where the entire movement of the bulk auxetic is determined by the phase angle 휃 between two links within the periodic pattern. Since an auxetic metamaterial tesselates the same pattern across its surface, as 휃 changes, the entire pattern will expand at once by symmetry, reaching a maximum expansion at 휃푚푎푥 (Fig. 2-1). By changing the linkage connections, we can bias this continuous expansion so that certain cells expand at different rates or in different directions, creating a net shear. In order to have a net shear on the structure, [30] found that only 2 symmetry groups out of the 17 wallpaper group tilings work. Specifically, 2222 – the symmetry group of four separate rotational centers of order 2 without reflections, and o – the symmetry group of only translational symmetries.
For normal auxetics, 휃푚푎푥 represents a symmetric point; any movement away from this point will cause the material to contract from this maximal expansion. This symmetric point introduces a line of reflection to the system, so this contraction can bias to the right or the left – a possible transition from its original shearing bias. The overall system thus becomes unhanded, as an auxetic can now continuously deform from one direction to its mirror. To make this a chiral system, we need to break this induced mirror symmetry at 휃푚푎푥. This results in right and left-handed versions of a given pattern which cannot transform into the other at any point on their auxetic trajectory. Some ways we can force this handedness include limiting joint angles or redesigning the pattern to no longer be symmetric at maximum expansion (ex. replacing a rectangle with a parallelogram in Fig. 2-1).
If we wrap a planar shearing auxetic around a cylinder, the net shear of the plane will manifest itself as a twist on the cylinder. This means that we can now control the auxetic expansion of the cylinder through rotation. Depending on what angle we wrap the shearing auxetic, we can change the ratio of auxetic expansion in the lateral and radial directions. To make a chiral auxetic cylinder, we can either use a handed shearing auxetic pattern or we can orient an unhanded shearing auxetic cleverly. Since we only care about breaking reflection symmetry at 휃푚푎푥, we just need
26 Figure 2-1: Overview examples of the auxetic trajectories for conventional auxetics, shear auxetics and handed shearing auxetics. As 휃 varies (arc in blue), the auxetic pattern expands and contracts, with maximum expansion occuring at 휃푚푎푥. While the top two auxetic classes have mirror symmetry at 휃푚푎푥, the bottom two do not, al- lowing those classes to maintain a single chirality throughout their trajectory. Figure originally appeared in [30]
27 to make sure that our unhanded shearing auxetic’s reflection lines do not coincide with the cylinder’s radial or lateral axes. This ensures that the cylinder as a whole lacks symmetry.
28 Chapter 3
Actuator Design
In order to create a soft robotic gripper that would avoid the inefficiencies and lack of robustness inherent to pneumatic-driven systems, we use HSAs as the base actu- ator. We chose to focus on HSAs because their intrinsic coupling between twisting with extension strongly motivates their use with direct-drive conventional motors. In this section, we discuss how HSAs can be used as an compliant electric actuator and provide examples of a linear actuator and four degree-of-freedom (DOF) robotic platform.
3.1 Paired Chiralities
A functional actuator needs to be able to move to a position and maintain that position under load. Although a single HSA cylinder can be twisted by hand to achieve a certain extension, this requires holding one end fixed relative to the other to achieve a net rotation across the cylinder. Although we can do this in certain settings, such as pushing a platform across rails, fixing one end is infeasible fora gripper scenario, where we want flexible movement. Without extra hardware, it seems unlikely that just one HSA cylinder can make an actuator. Rather than just using a single HSA, we instead realize that pairing HSAs of opposite chirality will resolve the net torque issue. If we connect the ends of a right- handed and left-handed HSA, each one serves as the “fixed point” for the other.
29 Applying a torque at the bottom of a cylinder will now create a net twist across the cylinder and enable extension (Fig. 3-1).
We also notice that this pairing configuration helps maintain position by creat- ing a self-locking structure. The right-handed cylinder wants to collapse by twisting clockwise, while the left-handed cylinder wants to collapse by twisting counterclock- wise. Since these two directions directly oppose each other, each cylinder will prevent the other from close. In other words, each HSA cylinder applies a counter-torque to the other, which allows the net extension to be maintained.
This paired configuration gives us the properties that we desired for a compliant electric actuator. We’ve outlined how position can be achieved and maintained with a motor (rather than pneumatics) by the interlocking nature of the paired HSAs. Also, since HSAs are a metamaterial, we can choose to make them out of a softer material and specifically choose our desired level of actuator compliance.
Figure 3-1: Schematic of how pairing handed shearing auxetics of different handedness create an actuator. If we constrain the pair on the top and counterrotate the cylinders against each other, each tube will expand, leading to bulk extension.
30 3.2 Materials, Methods and Fabrication
Now that we know what the desired layout of the actuators is, we now just need to design and fabricate the actuators – specifically, material selection and system integration. For simplicity, we’d like to make the HSAs out of a single material and actuate them as directly as possible.
3.2.1 Material Selection
In order for our auxetic metamaterial pattern to work on a continuous material, the base material must be able to support (1) rigid links and (2) flexure joints / living hinges. This comes from Sec. 2.2; the repeated tesselation of struts and joints provides the expansion characteristic of an auxetic. These constraints mean that there is a tradeoff in stiffness. If the material is too soft, the rigidity of the links is compromised and the angle of the auxetic trajectory won’t be maintained. However, if the material is too stiff, it will be difficult to create a joint that can sustain repeatedflexing without relying on external mechanisms. For example, we initially experimented with aluminum based on our successes in [30], which used spring steel and pin joints to validate its theory. However, we were unable to even make planar coupons out of aluminum as the necessary thickness to allow flexing was too small. The “joints” would either not move or only shift once before fracturing. Material selection also requires us to be mindful of our fabrication techniques. Since we are interested in cylinders for their direct coupling between twisting and expansion, we need a fabrication technique that can handle the precision and detail of our requisite geometric pattern on a curved surface. The fabrication techniques available to us that can manufacture high resolution patterns on a cylinder are CNC lathes, 3D printing, laser cutters with a rotary en- graver attachment. Due to simplicity and speed of fabrication, we primarily de- signed around the laser cutter. Turning a piece with a CNC lathe introduces a lot of headaches with fixturing, while 3D printing tends to severely limit the rangeof possible materials. However, we are still keeping these other fabrication techniques
31 in mind as we perform further material investigation. Given these material and fabric constraints, we experimented with several types of plastics, including acrylic, polypropylene, PETG and nylon. Although many of these materials seemed promising, especially the nylon, limitations in the precision with the laser cutter made some materials difficult to cut. Since all cuts had to bemade in one pass, some materials had a tendency to melt, artificially limiting the motion of the auxetics. An improved laser cutter system would enable a richer material design space and reach the full potential of HSA’s material and size agnosticism. We eventually settled on polytetrafluoroethylene (PTFE) as our base material. Although it was slightly unsafe to cut on the laser cutter, its high Young’s modulus made it the perfect fit for sustaining the requisite amount of flexing and expansion.
3.2.2 Fabrication
All handed shearing auxetics in this thesis were cut from 25.6 mm diameter PTFE tubes with a 1.58 mm wall thickness. We’d take an off-the-shelf PTFE tube (Mc- Master Carr) and cut out the relevant handed shearing auxetic pattern on a rotary engraver (PLS6.150D, Universal Laser Systems). The specific pattern that we cut is a strut version of the “handed by alignment” layout shown in Fig. 2-1. It can be partially seen in Fig. 4-1A. The cylinders used in Sec. 3.3 were cut to a length of about 140 mm, repeating the auxetic base pattern three times around the tube’s circumference. Once we settled on laser cutting PTFE, we had to make our own jig to precisely cut out HSAs. Typical rotary engravers are designed for engraving wine glasses, which are significantly larger and require less precision to cut than our PTFE tubes. We also needed to ensure that no tension was applied onto the PTFE tube; otherwise, the HSA piece could buckle as the laser cutter was differentially cutting some sections over others, creating a stiffness offset. Rather than use the given aluminum attachments for the rotary engraver (which was designed for wine glasses), we turned our own adapters on the lathe, which would set screw onto the existing shafts of the rotary engraver’s motor flats on the head
32 and tail stock. These two adapters were also connected by a set screwed internal sandblasted aluminum rod. This rod ensured that the tension was kept off of the workpiece and instead only placed on the rod. The PTFE tubes were held by a close sliding fit on the adapter’s internal diameter.
Note in Fig. 3-1 that the constraint level clamping the two HSA cylinder ends together is lengthening. This is because the auxetic properties of the HSAs means that the diameter of the cylinders increases on actuation. In order to avoid having a extensible constraint, we leave some uncut area on the top and bottom of each cylinder to serve as a “end cap” for the HSA pattern. This also gives us a consistent mounting point for components without needing to worry about expansion. Although this end cap will definitely affect the behavior of our system as we are not working with a continuous auxetic material, the effect should be minimal as long as the auxetic pattern is much longer than this end cap.
3.2.3 System Integration
Now that we have our HSA cylinders, we need to connect them and have them counter- rotate against each other. Creating counter torques on the two cylinders with a motor is as simple as connecting them with gears. These gears will apply opposing torques to each of the cylinders, allowing the HSAs to rotate against each other.
Notably though, this means that a constant external torque is required to maintain state as removing the torque would cause the HSAs to return to their unactuated state. Although we could use mechanism like a ratchet or worm drive to ensure that state is maintained without power, in the interest of simplicity, we accept this inefficiency.
We produce gears, shafts, gearplates and connecting end caps via 3D printing on a Stratasys Fortus 250mc 3D printer. The PTFE tubes are bolted into these caps and geared up to be driven by a multi-turn HS-785 HB servos. These servos were controlled either by an Arduino or Pololu’s Micro Mestro servo controller.
33 3.3 Actuator Applications
Now that we’ve established the theory and fabrication methods, we now can apply those findings to create compliant soft robotic systems without the complex driving hardware of pulleys or compressors. Making a compliant linear actuator follows directly from our discussion in Sec. 3.1, as HSAs directly couple linear extension with rotation. We can create a linear actuator by combining two HSAs with opposite handedness, using the geared struc- ture described in Sec. 3.2.3. Fig. 3-2 highlights both the extent of motion as well as the compliance of the system.
Figure 3-2: (A) Demonstration of a linear actuator made from handed shearing auxet- ics. Through a series of gears driven by a conventional servo motor, the two cylinders counterrotate against each other, creating extension. (B) This linear actuator is also quite compliant, allowing it to benefit from greater environmental interaction.
We can further expand on the concept of this linear actuator by combining multiple HSA pairs together. This allows us to use the same interlocking effect between the chiral cylinders within a HSA pair on a larger scale, by having pairs self-frustrate against each other. The simplest way to combine HSA pairs against each other, mechanically connecting one end of all of the cylinders and placing all of the actuators on the other. Actuating one of the HSA pairs will cause it to extend past the other HSA pair, creating an overall bending effect. Actuating both pairs causes a net vertical extension. Thus, this configuration essentially makes a new meta 2-DoF actuator – a degree-of-freedom for each original HSA actuator.
34 Figure 3-3: Demonstration of the full four degrees of freedom of the robotic plat- form. By composing two left-handed and two right-handed shearing auxetics, the platform can rotate in all directions as well as extend, depending on which cylinders are actuated. Figure originally appeared in [30]
A more complex way to combine multiple pairs together is by creating a two- by-two grid of HSA cylinders, alternating left and right-handed HSA cylinders in a checkerboard pattern. Each side of this pattern is a different left + right-handed HSA pair, making our structure implicitly composed of four linear actuators and implying that the structure will have four degrees of freedom. Indeed, as seen in Fig. 3-3, we see that the robotic platform can rotate in all directions and perform vertical extension. Extension is achieved by actuating all four cylinders, while rotation is achieved by actuating any two cylinders. More specifically, bending is achieved by actuating one side of the checkerboard, a similar modality to the 2-DoF actuator described earlier. In-place twisting is achieved by actuating the cylinders along the diagonal, as a large net torque is placed on the structure.
One thing to note that happens with these actuators is the presence of helical instability when overactuated. This helical instability manifests itself as an internal twisting – either of a single cylinder buckling in on itself, or of a cylinder twisting around the other cylinder of its pair 3-4. Although this behavior occurs in the linear actuator as well, this behavior is more easily seen in the 4-DoF platform due to the larger range of motion and extra stability from the greater number of actuators.
Although we have not fully investigated the cause of the helical instability, the repeatability of when the instability occurs and how it manifests itself suggests that
35 it is caused by some repeatable physical constraint and not a stochastic or fatigue process. When the actuators are extended closer to the point of maximal expansion, the end caps or other HSA cylinders may provide a strong enough boundary condition to cause this behavior. The buckling inwards may also be further exacerbated by the relatively thick beam width of the individual struts that make up the HSA pattern. These and other manufacturing variations may cause one cylinder in a pair to be more compliant than the other, inducing that one to go into a strange buckling mode. Regardless of the cause, we must keep helical instability in mind as we design, as our HSA actuators may be forced to work in this regime.
Figure 3-4: When the handed shearing auxetic (HSA) cylinders are overactuated, helical instability can occur where the cylinders twist in on themselves. This typically happens when either (A) the HSAs approach their state of maximal expansion or (B) when an external constraint adds extra force to the system.
36 Chapter 4
Gripper Design
Similar to some of the soft grippers described in Sec. 2.1.2, we modify the design of our actuator created in Ch. 3 slightly in order to use them directly as grippers. By adding a strain-limiting constraint layer like [20], we turn an HSA pair’s linear extension into an out-of-plane bending. We then put two bending pairs together to form the fingers for our compliant gripper.
4.1 Constraint Layers
Current soft robotic grippers shape their overall bulk movement by adding in a phys- ical limit to a regular actuator, either through increased stiffness or a hard stop. This can vary from directly adding a strain limiting layer to one side of a pneumatic finger, limiting radial expansion via fiber-reinforcement in a McKibben actuator, or using cables’ tension to force a movement direction for a tendon-based system [40, 14, 41]. Finding an appropriate constraint limit for the HSAs is not as simple as just adding a hard constraint. Since the cylinders twist against each other, any physical constraint we add must rotate with the HSAs. Naively adhering a strain limit to the surface of the HSA cylinders would result in that layer simply being deformed and sheared off from the surface. Instead, we recall from Sec. 2.2.2 that the movement ofthe HSA is determined by the angle 휃 between two links in its periodic pattern. Halting the movement of the HSA is just a matter of creating internal angular constraints to
37 prevent certain regions of the HSA from expanding. For our system, we decide to create the internal angular constraints along a line parallel to the main diagonal of the HSA unit cell (Fig. 4-1A). Going parallel to the pattern allows us to avoid removing the flexural joints needed for auxetic expansion, while still providing the desired strain constraints. Due to how the twist works, this diagonal pattern will result in a straight pattern along the axial direction once the cylinder is at maximum expansion. In effect, this constraint layer becomes the inner radius of the finger, defining the radius of curvature of bending (Fig. 4-1B, C).We also include constraints along the top and bottom of the HSA pattern, to better ease the transition from the HSA pattern to the rigid uncut “caps” of the PTFE tubes discussed in Sec. 3.2.3.
4.2 Fabrication and System Integration
Similar to the HSA fabrication outlined in Sec. 3.2.2, we cut from 25.6 mm diameter PTFE tubes with a 1.58 mm wall thickness. In order to provide a direct compari- son against a pneumatic gripper in Sec. 5.3, most experiments were conducted with fingers that were 130 mm in length with three HSA base units repeated aroundthe circumference. This is because this is approximately the size of the unactuated state of our comparison pneumatic gripper from [18]. Some validation experiments were instead performed with smaller cut tubes (length: 60 mm) with six base units repeated around the circumference instead. Although this length is drastically shorter, it gave a smaller bend radius that matched the actuated bend radius of [18]. This is because HSA cylinders couple twisting with extension, so the fingers actually gain significant length over the course of actuation, asseenin Fig. 4-1C. Unless otherwise specified, it should be assumed that any reported results were taken from the 130 mm fingers. As in Sec. 3.2.3, we 3D printed a variety of components in order to connect the HSA cylinders to each other and to the servo. For the gripper, we also 3D printed mounting adapters to attach our gripper to the hand of the Rethink Robotics’ Baxter
38 Figure 4-1: Demonstration of how (A) adding a constraint layer to the base handed shearing auxetic pattern causes out of plane bending fingers. The red circles show the diagonal constraint while the blue circles show the end cap top constraint. (B) Shots from head-on and (C) in profile reveal how the constraint layer goes from a diagonal wrap to a straight internal radius of the bending circle.
39 robot (Fig. 4-2). This involved moving the servo to the side of the fingers and adding a silicone-covered palm between the fingers, to provide another point of contact similar to [18]’s design. Contact friction is extremly important for improved manipulation; this is an issue since the HSA fingers are made from PTFE which is very low friction. To increase our fingers’ frictions, we wrapped each finger in a silicone glove. The glove wasmadeby folding a bag-like shape out of a thin silicone sheet (0.8 mm), epoxying it closed with room-temperature vulcanizing silicone sealant, and placing it over the finger. The glove was attached to the free end of the HSA finger by a non-permanent adhesive, allowing it to follow the finger’s deformation but not slide off. We also placed a3.2 mm strip of neoprene foam between the HSA tubes and the glove to increase contact surface area between the finger and the grasped object. The glove holds the foamin place aginst the HSA cylinders, especially when the finger is pressed up against an object.
Figure 4-2: Overview of the gripper design. Each finger is made out of a pair of handed shearing auxetic cylinders that can bend out of plane. These actuators are driven by a motor to bend. A silicone glove, palm, and neoprene foam add more points of contact and friction. Figure originally appeared in [9].
40 Chapter 5
Experimental Results and Characterization
In this section, we characterize the electric actuators built in Sec. 3.2.3 and 4.2. By characterizing the mechanical performance of the base actuator, we can evaluate our qualitative claims about the nature of the HSA design. We then investigate how well these properties hold up for our gripper, culminating in a direct comparison against the state-of-the-art soft pneumatic gripper described in [18].
5.1 Characterization of Actuator
Before we can characterize the HSA pair-based actuators, let’s further characterize a single HSA cylinder on its own. One claim that we’ve been making throughout this thesis is that HSAs naturally couple a rotational twist with linear motion. How tight is this coupling? To measure this, we conduct a tensile hysteresis test on a 92 mm long HSA cylinder, cyclically pulling the sample to 80 mm extension at a rate of 50 mm / min. In one experiment, we took a normal cyclic loading test, but in the other experiment, we added an adapter with a bearing to the HSA mounting setup, allowing the cylinder to rotate freely as it is being extended. For each test condition, we perform the test three times each, reporting the average of all three trials and the standard deviation
41 as error bars in Fig. 5-1.
Figure 5-1: Cyclic tensile loading of a handed shearing auxetic cylinder when rotation is allowed (red curve) and when the cylinder is held in place (blue curve). When rotation is allowed, significantly lower stiffness is reported (193 ± 0.3 N/m vs. 285 ± 0.7 N/m), revealing how the HSA naturally couples twisting with extension.
We found that when the HSA is allowed to freely rotate under extension, a lower stiffness is reported (193 ± 0.3 N/m) than in the static, no-rotation case (285 ± 0.7 N/m). This confirms that twisting the HSA allows further extension to occur, asless strain is placed on the HSA structure when it is pulled with rotation rather than just straight pulled. This also suggests that in future work, if we can control the extent of allowable rotations for the HSA cylinders, we’ll be able to control the effective stiffness of the element. Given the strong hysteresis present in this curve, we note that the HSA system is losing a significant amount of energy each cycle, possibly due to the plastic defor- mation of the flexural joints. However, we also note that the loading portion ofthe curves are extremely linear, suggesting that HSAs may act as an elastic spring-like elemnet when held at a specific angle. This also hints at future work at deploying HSAs as adjustable length springs. Now that we know how a single HSA cylinder deforms, we turn our attention to quantifying the behavior of the linear actuator and 4-DoF platform created in
42 Table 5.1: Mechanical Properties of Handed Shearing Auxetic Actuators Linear Actuator (Fig. 3-2) Single HSA cylinder 30.8 g System Weight 351 g (w. servos) Max Extended Length (in 푦) 217 ± 7.8 mm Min Extended Length (in 푦) 144 ± 0.4 mm Robotic Platform (Fig. 3-3) System Weight 925 g (w. servos) Max Extended Length (in 푦) 238 ± 0.5 mm Min Extended Length (in 푦) 148 ± 0.1 mm Max Rotation about 푥 45 ± 4.2∘ Min Rotation about 푥 -54 ± 2.5∘ Max Rotation about 푧 53 ± 2.6∘ Min Rotation about 푧 -52 ± 0.86∘ Max Rotation about 푦 144 ± 27∘ Min Rotation about 푦 -138 ± 11∘
Sec. 3.2.3. We quantify the maximum range of both systems with an OptiTrack motion capture system. We place markers on the 3D-printed top and bottom plates of both systems, creating two sets of coordinate systems. This allows us to measure the overall change in angle and extension by seeing how much the top reference frame translates / rotates with respect to the bottom refreence frame. Servos were manually driven until the internal living hinges of the HSA cylinders were extended or compressed fully, preventing further extension or rotation (ex. as seen in Fig. 3- 4). Three trials were conducted for each measurement and summarized in Table 5.1. In the table, 푥 refers to the axis coming out of the page, 푦 refers to the axis of vertical extension, and 푧 points to the right of the page (to complete the right-handed coordinate system). A visualization of these axes can be seen in Fig. 5-2.
The HSA’s extreme rate of length change and helical instability made it difficult to ensure consistent motion, especially for the rotation measurements. This doubt about actually achieving the maximum achievable range may explain why the measurements for the 4-DoF’s rotation about 푦 have such high variance. The deviation between the 푥 and 푧’s ranges is also particularly striking, as they should be similar due to symmetry.
43 Nevertheless, despite these limitations, both the linear actuator and 4-DoF plat- form demonstrated an immense amount of range. Both systems were able to extend by 60% of their original length. Meanwhile, the 4-DoF Platform could bend (pitch / roll) by 100∘ and twist in on itself (yaw) by an impressive 280∘. These results offer a lot of potential for future soft robotic actuators.
5.2 Characterization of Gripper
After characterizing the linear version of the actuators, it’s time to see how the HSA behavior changes upon adding a constraint layer. In this experiment, we use the 60 mm finger with six repeated base units in order to have a similar grasp profileas other soft robotic grippers. We perform a similar OptiTrack characterization as in the above section, tracking the top and bottom caps of the finger in order to measure the overall angle change. We record the measured angle deformation while cyclically stepping through the finger’s minimal and maximal expansion states. The maximal expansion state corresponds to the fingers being closed around an object and occurs right before when the finger starts undergoing helical instability. Likewise, the minimal expansion state corresponds to the fingers being the most spread apart and corresponds to a zero angle between linkages (i.e. struts are jammed against each other). We conduct three trials, cycling through open-close-open formations. This gives us two datapoints per trial, which we then take the mean and standard deviation of for each servo position. Across all trials, we find that we are able to detect three different regimes in the finger’s motion (Fig. 5-2). At first, from 0 to 5 degrees, the initial increasein servo rotations does not affect the end effector pose position significantly. This lack of movement is probably due to needing to make up distance from backlash and the difficulty in detecting changes in strain / stress from motion alone. This “closed” regime appears on our graph as a near flat region, ranging from 0∘ to −10∘ of bending angle. This negative bending angle is an artifact of calibrating the compared angle at finger rest state rather than maximal contraction, as the natural rest state ofthe
44 fingers occurs at roughly 3 degrees of servo rotation.
Next, as the servo rotates from 5 to 13 degrees, we see a linear elongation as the bending angle ranges from 0∘ to 25∘. This linear elongation is expected as the strain limiting layer essentially adds a set inner radius for the finger to bend along, as a constant curvature constraint. Finally, past 13∘ of servo rotation, the helical instability regime starts coming in, twisting an almost unusuable amount at the 19 degree mark. Although we see a bending angle of nearly 45 degrees, the nearly 20 degrees of pitch difference makes it difficult to actually leverage that severe bend. However, this does suggest that if the helical instability can be mitigated, these bending HSA actuators have great potential for their linear response and wide range.
Figure 5-2: Motion capture results of the movement of a handed searing auxetic actuator pair with an added constraint layer to enable out-of-plane bending. Figure originally appeared in [11]
45 5.3 Comparison to Pneumatic Soft Gripper
Armed with a strong sense of the kinematics of our HSA-based actuators, we now compare our motor-driven approach against a pneumatically-actuated soft gripper originally presented in [18]. This gripper has four Pneunet-style fingers: silicone fingers cast with internal air bladders and preferential bending from intrinsic strain layers (Fig. 5-3). Each finger was molded from the platinum-cure silicones DragonSkin 10 and DragonSkin 20A (Smooth-On) and actuated by a Concentric Glideforce LACT2P pneumatic linear actuator controlled by a Pololu Jrk Motor Controller. Each finger also had 2-3 added gecko-inspired adhesive patches (first reported in [17]), in an attempt to significantly increase the hand’s static friction. For the sake of consistency, we used the same silicone-covered palm that we used for the HSA-based gripper for the pneumatic gripper rather than the full EcoFlex 00-10 silicone palm used in [18].
Figure 5-3: (A) Overview of pneumatic and handed shearing auxetic-based grippers, alongside their driving hardware. Closeups of the (B) pneumatic hand and (C) handed shearing auxetic grippers reveal their different morphologies and grapsing behavior. Figure originally appeared in [9].
46 We mount both hands onto the Rethink Robtics’ robot, Baxter, and contrast the two in terms of mechanical performance / robustness, grasping success rate, power efficiency. Our experimental findings are summarized in Table 5.2.
5.3.1 Mechanical Performance
Characterizing the mechanical performance of both systems involves directly measur- ing static properties (ex. dimensions, fabrication time) as well as evaluating more dynamic behavior (ex. bending radius, puncture resistance). We designed the HSA fingers to have a similar dimension to the pneumatic fingers back in Sec. 4.2 in order to have a more direct substitutable comparison. Indeed, the two fingers types are about the same size with similar surface areas intended to contact grasped objects. However, the pneumatic actuator system is significantly larger and bulkier than the two servos needed for the HSA gripper. This is a direct result of the discussion in Sec. 2.1.1 of the large infrastructure required to electrically move air under large pressures. Despite their similar size, the pneumatic grippers take significantly longer to make than the HSA grippers. For both fingers, we ignore the time to create the ancillary 3D printed parts as these are not the primary focus of either gripper and can be reused between fabrication runs. This is particularly true for the 3D printed mold parts for the pneumatic gripper, which have a high upfront cost to design but are fast to reuse for future molds. Based on the process described in [18], we estimate the entire process to take about 5 hours to produce a finger – 4 hours to mold and cure the DragonSkin 20A silicone, 30 minutes to mold and cure the DragonSkin 10A silicone, and 30 minutes for assembly. Although most of the time is spent waiting rather than active work, the time delay is significant, especially since the composite nature of the pneumatic gripper means that there is no way to parallelize production. The DragonSkin 10A curing can only occur after the DragonSkin 20A silicone is completed. Meanwhile, we estimate the fabrication time for a single HSA finger to be 1.5 hours – 30 minutes to laser cut each HSA cylinder, and 30 minutes for assembly.
47 Table 5.2: Comparison of Pneumatic vs. Handed Shear Auxetic Grippers Pneumatic Electric HSA Mechanical Properties Unactuated Finger 120 mm x 27 mm x 20 130 mm x 30 mm x 67 Dimensions mm mm Finger Weight 71.0 g 59.4 g Actuator Dimensions 370 mm x 95 mm x 110 50 mm x 28 mm x 58 mm mm Actuator Weight 1160 g 105.8 g Radius of Finger at 35 mm 75 mm Maximum Curvature Approximate Fabrication 5 hr (silicone casting) 1.5 hr (laser cutting) Time Laceration Resistance High High Puncture Resistance Low High Grasping Tests Grasp Success Rate - 72% 72% Total Grasp Success Rate - 84% 80% Regular Geometry Grasp Success Rate - 54% 62% Irregular Geometry Gripper Power Consumption Peak Power Usage 4.81 A @ 12 V 1.08 A @ 5V Energy Required to 107.4 J ± 1.04 J 4.92 ± 0.23 J Close Gripper Time to Close Gripper 2.90 ± 0.05 s 1.48 ± 0.05 s Power Required to 1.21 ± 0.0023 W 5.32 ± 0.04 W Maintain Closed State Energy Required to 93.5 ± 6.12 J 4.67 ± 0.22 J Open Gripper Time to Open Gripper 2.82 ± 0.02 s 1.42 ± 0.04 s
48 In terms of dynamic properties, we note that the HSA fingers have a minimum radius of curvature that is nearly twice as large as that of the pneumatic gripper. This is partially due to the difference in base gripper material compliance, as the pneumatic gripper’s silicone is is significantly more soft than the HSA gripper’s PTFE. However, as discussed in Sec. 4.2 and measured in Sec. 5.2, cutting the HSA fingers to a smaller length and repeating the pattern a greater number of times results in comparable radiuses of curvature. It also bears noting that due to the lower fabrication time and repeated nature of the auxetic pattern, it is significantly easier to make these sorts of modifications to the HSA system than it is to the pneumatic system. Shrinking the auxetic pattern and performing another laser cutting job is much faster than re-designing and re-printing a casting mold.
Robustness against Mechanical Damage
To evaluate mechanical robustness, laceration and puncture damage was applied to both grippers (Fig. 5-4). To get a sense of how much damage was needed to stop gripper functionality, we repeatedly performed these damage actions, checking af- ter each action that the gripper still worked as intended. The laceration damage was intended to simulate incidental contact with sharp objects and was modeled by scraping a sharp can lid against the internal curve of a finger. Puncture damage was intended to simulate severe single points of failure, highlighted in Sec. 2.1.1 as an area of concern for fluidic actuators. This was modeled by taking a 1 mm diameter pin and puncturing the finger’s internal curve. Since both grippers have a large amount of bulk material / empty space that are not critical to the operation, care was taken to prioritize damage to critical areas. This meant focusing on internal bladders for the pneumatic gripper and internal struts for the HSA gripper. Both grippers were fairly resistant to laceration damage. The compliance of the HSA gripper’s silicone glove and the pneumatic gripper’s bulk material made it dif- ficult to really gain purchase on the gripper body. No effect to grasping abilityor actuator performance was noted, even after multiple (20) lacerations. However, for puncture damage, the HSA gripper demonstrated much more robust-
49 Figure 5-4: Demonstration of puncture resistance of a handed shearing auxetic grip- per. (A) Normal operation is indistinguishable from (B) the gripper after repeated laceration damage or (C) repeated puncture damage. Figure originally appeared in [10]
50 ness. The pneumatic finger failed after a single puncture, since the internal bladder was prioritized. By weakening the walls of the pressure changes, the puncture wound caused that weakened section to deform differently than the rest of the gripper, caus- ing a bubble to form and rupture. By contrast, the HSA finger performed normally, even after 20 punctures that prioritized the internal struts. The comparatively larger stiffness of the PTFE made it difficult to stab the needle all the waythroughand cause lasting damage. Instead, the only real damage was a perforation of the outside silicone glove. We do note that while the HSA gripper seems fairly robust against laceration and puncture damage types, it is probably more susceptible to slicing cuts. Since the HSA is reliant on its geometric pattern, any cuts that broke those internal features could prevent the twisting-extension coupling from occurring. It should be noted though that this slicing damage would likely cause the pneumatic gripper to experience the same rupture failure as for puncture, due to the same weakened wall argument as above. While not all links are necessary for the HSA cylinder to expand, a single weakened wall in a pneumatic finger can result to catastrophic failure.
5.3.2 Grasping Performance similar grasping performance – 32 objects, 72% success To evaluate how the grippers were able to function in an actual application, grasp- ing tests with both grippers were conducted. Each hand was mounted to a Rethink Robotics Baxter robot, which was programmed to reach and grasp objects at a specific location. Since we were interested in evaluating the gripper’s mechanical properties and not the general manipulation problem, we manually configured the grasp orien- tation and height of each object for Baxter’s pre-programmed motion path. Each experiment followed the same pattern; we’d set an object at Baxter’s specific grasp point, using modeling clay to elevate the object if necessary. Baxter would then approach the object horizontally and grasp around it. It would then lift the object, rotate its wrist back and forth to ensure a tight grasp, and return the object. Five manual reconfigurations / drops would be attempted before it was decided thatthe
51 gripper was unable to pick up the object. Code for these experiments can be found in App. A. 32 objects were used in these experiments – a combination of household groceries and objects from the YCB manipulation object dataset [7]. These objects were chosen for diversity in material properties, such as stiffness, geometry, weight, and size. All objects used can be seen in Fig. 5-5. Both grippers grasped 72% of the tested objects, demonstrating similar grasp performance. The pneumatic gripper was better at grasping larger objects that it could envelop within its grasp (ex. wine bottle, fake banana). This is possibly due to its smaller radius of curvature allowing it to exert the greater lateral grasping force needed to hold larger objects. Meanwhile, the HSA gripper was better able to grasp small irregular objects (ex. diagonal cutters, broccoli). This suggests that when the HSA gripper was able to get a purchase on objects, it may have conformed more closely, and thus been able to handle irregular geometries. Both grippers had difficulty grasping objects requiring a precision grasp style, probably because both have a much larger radius of curvature than what is needed for precision grasps. The grippers also had difficulty grasping heavy objects (ex. mustard bottle) as their inherent compliance means that it’s also easier for heavy objects to deform the fingers and slip out of their grasp.
Figure 5-5: Array of objects used in grasp testing. (A) Objects successfully grasped by both grippers. (B) Objects only grasped by the handed shearing auxetic based gripper. (C) Objects only grasped by the pneumatic gripper. (D) Objects that were not able to be grasped by either gripper. Figure originally appeared in [9]
52 5.3.3 Power Efficiency
Finally, we compare both grippers on energy efficiency by measuring how much power is needed for each actuator type to perform a grasping motion. Power consumption was measured by powering each gripper’s actuators with a DC power supply (Tek- tronix PWS4000). This allowed us to measure the current draw as the gripper open and closed, enabling us to analyze peak power usage and overall energy consumption. For each gripper, measurements of each of the servos / linear actuators were taken separately and then added together to provide a full picture of energy consumption. As expected, the motor-driven HSA gripper was significantly faster and used less power than the pneumatic system, as no electrical signal vs. fluid flow translation was needed. The HSA gripper required 20 times less energy to open and close than the pneumatic gripper, while also performing these actions in half the time. The HSA gripper did, however, require 5 times as much power to maintain a closed state as the pneumatic gripper. This is primarily because of the lack of a latching mechanism to passively maintain state, as discussed in Sec. 3.2.3. Nevertheless, the HSA gripper provides significant energy savings for compliant grasping.
53 54 Chapter 6
Discussion
In this thesis, we achieved our goal of creating compliant electrically-driven actuators for soft robotics. We introduce HSAs as a new building block for actuator design, able to maintain the adaptability and continuous deformation of current soft robots while avoiding the energy inefficiency and low mechanical resilience inherent with pneumatic or other popular actuation techniques. By converting rotation into linear motion just from intrinsic geometry, HSAs are able to create complex motion without the typically associated rise in complexity of driving schemes or actuation methods. HSAs are a metamaterial which imbue traditional auxetics with a set chirality and a net shear. These additional properties are achieved by breaking certain planar symmetries within their internal geometric structure to create a strong coupling between twisting and extension. Traditional motors and servos can thus be used to apply rotation to get straightforward and direct linear motion. This inherent reliance on intrinsic geometry allows the theory of HSAs to work across different materials and scales, as well as make it easy to modify with new variations. Out of plane bending was simply achieved by adding a small constraint to this geometric pattern, a variation that did not require a significant repeat of design and fabrication efforts that say, a new cable structure or pneumatic- based mold design would need. We’ve highlighted how versatile this geometric approach can be, creating linear actuators, 4-DoF robotic platforms, and robotic grippers just through simple varia-
55 tions of the base geometric pattern or actuator configurations. Pairing two HSAs of opposite chirality and applying a counter-rotation to both, the entire pair will move together as each cylinder prevents the other from collapsing back to rest state. These actuators have a significantly useful range of motion – 60% extension for thelinear actuator, over 100∘ of rotation in all directions for the 4-DoF platform, and 25∘ of bending radius for the gripper’s fingers. Furthermore, we have demonstrated that HSA-based grippers provide comparable grasping performance to other soft grippers, while simultaneously using simpler fabrication techniques, consuming less energy, and demonstrating a greater robustness against mechanical damage.
6.1 Lessons Learned
In addition to the technical contributions outlined above, many other lessons were learned about the process of conducting research. Although I am proud of this work’s results, focusing too narrowly on the end products of the research can minimize the important takeaways learned along the way. The following things should be kept in mind for the future – both for me, as I start settling into a more focused research role, and for you, the prescribed reader curious about either the social process of research or what pitfalls may lie in store for the unprepared.
1. Deadlines are useful, but you shouldn’t die to make them. Much of the work in this thesis was performed in a compressed period from Oct. to Dec. 2018, coinciding with the announcement (and subsequent deadline) of the first ever soft robotics conference. While I’m happy that I was able tofinish and present this work in time for the conference, it came at significant cost to personal health and well-being.
This fed back into more rushed research, resulting in clear sacrifices to safety and engineering robustness as sleep-deprived me was less effective at analyzing a situation. Technical debt accumulates easily and is more easily incurred when not operating at peak biological conditions. Just as soft robotics asks that we
56 start considering the body of the robot in our design process and its potential advantages with the environment, so too should we remember the body of the researcher making the meta-level decisions in the design.
2. The design process takes longer than expected, especially when you’re creating and designing an entirely new class of things. Although the materials and processes I used in this research were fairly off-the-shelf or estab- lished, the work required to integrate all of these components into a functional system is significant. Even establishing a protocol for slightly non-standard techniques, like using the rotary engraver as a cutting device for smaller pieces, requires effort to ensure a well-designed process. As tempting as it is tospeedup the process by implementing hacky solutions, you should always keep in mind that someone later down the line (probably yourself) will eventually need to fol- low the same trail and get the same results. Again, technical debt accumulates easily and must inevitably be paid.
3. Negative results are still results. Although it may feel somewhat te- dious, the process of material selection or engineering a more robust fabrication pipeline provides insights into possible limtations of your current design. I am grateful that this thesis actually gives me a place to highlight the work that went involved in these refinements, as this fine-tuning often goes under-reported and underappreciated. However, external validation of this “graduate student gra- dient descent” is unnecessary so long as you keep careful notes and don’t repeat the same mistakes in the future.
6.2 Future Work
In the future, we are excited on expanding on HSAs as a platform for further soft robotic work. Now that we have a directly electric-driven system, tighter integra- tion with sensing modalities is now possible. Rather than attempt to create hybrid pneumatic-electric systems, our sensorization can be more direct and possibly en-
57 able true proprioception. These enhanced sensing capbilites could help flesh out our grasping demonstration into a full grasping pipeline, especially if coupled with current advances in computer vision. As highlighted in Sec. 3.2, significant work is still left in material selection forthe base HSA material. This is especially critical if we’d like to deliver on the material- agnostic nature of the metamaterial basis for HSAs. Since many of the materials discussed were passed over for pure fabricability reasons, other fabrication techniques beyond the laser cutter should be considered. As HSAs become a more standard- ized part of an engineering toolkit, the production repeatability should become more standardized as well. As more materials become available for use with the HSAs, a better understanding of how to design the flexural joints within the HSA’s geometric structure is needed. The current joints are the product of manual iteration and optimization for PTFE’s material properties, a process which will not scale well to other materials. Thin-beam flexural joints are a notoriously difficult concept to analyze from a mechanical and numerical simulation perspective, so creating a computational design tool would be a significant accomplishment. Any design tools built to understand a single flexural joint could also be applied to the structure at large, creating more optimized tesselated patterns that follow the desired symmetry group or enabling non-engineers to design their own HSA systems with lower cost or more easily accessible materials.
58 Appendix A
Code
aux_gripper_launch.launch
1
ExperimentController.py
1 #!/usr/bin/env python 2 3 import sys , os 4 sys.path.insert(0, ’/home/drl/ros_ws/src ’) 5 from time import s l e e p 6 from BaxterController import BaxterController 7 import rospy 8 import baxter_interface 9 from T r a j e c t o r y import Trajectory , getTrajPoint 10 from h e l p e r s import * 11 from std_msgs .msg import S t r i n g 12 13 ##### ROSPY CONFIGURATION 14 b l o c k i n g = True 15 limbName = ’ r i g h t ’
59 16 useAuxHands = Fa lse 17 18 rospy.init_node( ’aux_gripper_test ’) 19 controller = BaxterController(limbName = limbName, printDebug=False) 20 hand_pub = rospy.Publisher("aux_finger_channel", String , queue_size=10) 21 22 # Clear out trajectory restrictions 23 # rospy.set_param(’joint_trajectory_action_server/left_s0_trajectory ’, ’ −1 ’) 24 # Reset trajectory restrictions 25 # rospy.set_param(’joint_trajectory_action_server/left_s0_trajectory ’, ’0.35’) 26 27 28 ##################################### 29 # TRAJECTORY DEFINTIONS 30 ##################################### 31 32 # s0: increasing moves outward, −45 is straight in front 33 # w0: increasing moves inward, 0 is straight out from arm 34 35 # s1: increasing moves arm down, 0 is horizontal 36 # e1: increasing moves arm down, 0 is horizontal 37 # w1: increasing moves arm down, 0 is straight to arm 38 39 # for straight wrist, want s1+e1+w1 = 0 40 41 # temp declaration to get variables with the right scope 42 t a b l e N e u t r a l = 0 43 tableGrab = 0 44 l i f t P o s = 0 45 46 # Neutral on table 47 i f limbName == ’left ’: 48 tableNeutral = OrderedDict([(’s0’, −2) , 49 ( ’ s1 ’ , 33) , 50 ( ’ e0 ’ , −4.5) , 51 ( ’ e1 ’ , −3) , 52 ( ’w0 ’ , 99) , 53 ( ’w1 ’ , −90) , 54 ( ’w2 ’ , −60) ] ) 55 56 tableGrab = OrderedDict([(’s0’, −21) , 57 ( ’ s1 ’ , 30) , 58 ( ’ e0 ’ , −4.5) , 59 ( ’ e1 ’ , −3) , 60 ( ’w0 ’ , 99) ,
60 61 ( ’w1 ’ , −90) , 62 ( ’w2 ’ , −60) ] ) 63 64 liftPos = OrderedDict([(’s0’, −9) , 65 ( ’ s1 ’ , 11) , 66 ( ’ e0 ’ , −5) , 67 ( ’ e1 ’ , −3) , 68 ( ’w0 ’ , 90) , 69 ( ’w1 ’ , −80) , 70 ( ’w2 ’ , −80) ] ) 71 e l i f limbName == ’right ’: 72 tableNeutral = OrderedDict([(’s0’, 14), 73 ( ’ s1 ’ , 12) , 74 ( ’ e0 ’ , −5) , 75 ( ’ e1 ’ , 30) , 76 ( ’w0 ’ , −95) , 77 ( ’w1 ’ , −90) , 78 ( ’w2 ’ , 40) ] ) 79 80 tableGrab = OrderedDict([(’s0’, 32), 81 ( ’ s1 ’ , 10) , 82 ( ’ e0 ’ , −5) , 83 ( ’ e1 ’ , 30) , 84 ( ’w0 ’ , −95) , 85 ( ’w1 ’ , −90) , 86 ( ’w2 ’ , 40) ] ) 87 88 liftPos = OrderedDict([(’s0’, 12), 89 ( ’ s1 ’ , −6) , 90 ( ’ e0 ’ , 0) , 91 ( ’ e1 ’ , 27) , 92 ( ’w0 ’ , −85) , 93 ( ’w1 ’ , −90) , 94 ( ’w2 ’ , 60) ] ) 95 else : 96 raw_input( ’SOMETHING IS VERY WRONG’ ) 97 98 99 ##################################### 100 # MAIN PROGRAM 101 ##################################### 102 103 # Move into position 104 controller.setJointAngles(getTrajPoint(deg2rad(tableNeutral), limbName + ’_’), blocking=True)
61 105 hand_pub . p u b l i s h ( ’ o ’ ) 106 # #openGripper 107 raw_input(’press enter when object in position ’) 108 109 while raw_input(’Ready to test? (y)/n ’).lower() != ’n’: 110 t r a j = T r a j e c t o r y ( limbName ) 111 totalTimeMoved = 0 112 t r a j . stop ( ) 113 t r a j . c l e a r ( limbName ) 114 115 totalTimeMoved += 0 . 2 5 116 traj .add_point(getTrajPoint(deg2rad(tableNeutral)), totalTimeMoved) # prevent jerk 117 totalTimeMoved += 2 118 traj .add_point(getTrajPoint(deg2rad(tableGrab)) , totalTimeMoved) 119 t r a j . s t a r t ( ) 120 print ’waiting for movement start ’ 121 while traj.result() i s not None : 122 s l e e p ( 0 . 0 0 1 ) 123 # wait for motion to end 124 i f b l o c k i n g : 125 print ’waiting for movement end’ 126 while traj.result() i s None : 127 s l e e p ( 0 . 0 0 1 ) 128 129 i f useAuxHands : 130 hand_pub . p u b l i s h ( ’ c ’ ) 131 else : 132 133 134 135 136 s l e e p ( 0 . 5 ) 137 138 # Raise and shake object 139 totalTimeMoved = 0 140 t r a j . stop ( ) 141 t r a j . c l e a r ( limbName ) 142 143 totalTimeMoved += 0 . 2 5 144 traj.add_point(getTrajPoint(deg2rad(tableGrab), limbName + ’_’), totalTimeMoved) # prevent jerk 145 totalTimeMoved += 2 146 traj.add_point(getTrajPoint(deg2rad(liftPos), limbName + ’_’), totalTimeMoved) 147 totalTimeMoved += 1 148 l i f t P o s [ ’w2 ’ ] −= 45
62 149 traj.add_point(getTrajPoint(deg2rad(liftPos), limbName + ’_’), totalTimeMoved) 150 totalTimeMoved += 1 151 l i f t P o s [ ’w2 ’ ] += 90 152 traj.add_point(getTrajPoint(deg2rad(liftPos), limbName + ’_’), totalTimeMoved) 153 totalTimeMoved += 1 154 l i f t P o s [ ’w2 ’ ] −= 45 155 traj.add_point(getTrajPoint(deg2rad(liftPos), limbName + ’_’), totalTimeMoved) 156 # Return object to initial position 157 totalTimeMoved += 2 158 traj.add_point(getTrajPoint(deg2rad(tableGrab), limbName + ’_’), totalTimeMoved) 159 t r a j . s t a r t ( ) 160 print ’waiting for movement start ’ 161 while traj.result() i s not None : 162 s l e e p ( 0 . 0 0 1 ) 163 # wait for motion to end 164 i f b l o c k i n g : 165 print ’waiting for movement end’ 166 while traj.result() i s None : 167 s l e e p ( 0 . 0 0 1 ) 168 169 170 # Reset for next test 171 hand_pub . p u b l i s h ( ’ o ’ ) 172 s l e e p ( 0 . 5 ) 173 174 totalTimeMoved = 0 175 t r a j . stop ( ) 176 t r a j . c l e a r ( limbName ) 177 178 totalTimeMoved += 0 . 2 5 179 traj .add_point(getTrajPoint(deg2rad(tableGrab)) , totalTimeMoved) # prevent jerk 180 totalTimeMoved += 2 181 traj .add_point(getTrajPoint(deg2rad(tableNeutral)), totalTimeMoved) 182 t r a j . s t a r t ( ) 183 print ’waiting for movement start ’ 184 while traj.result() i s not None : 185 s l e e p ( 0 . 0 0 1 ) 186 # wait for motion to end 187 i f b l o c k i n g : 188 print ’waiting for movement end’ 189 while traj.result() i s None : 190 s l e e p ( 0 . 0 0 1 ) 191 192 os.system(’rosnode kill /joint_trajectory_action_server ’)
63 GripperControl.ino
1 #include
64 43 else i f ((inByte == 99)) { 44 Serial.println("Close"); 45 closeHand ( ) ; 46 } 47 inByte = 0 ; 48 } 49 // runThroughRange(&leftFinger ,10); 50 } 51 52 void openHand() { 53 for ( int i = 0; i < nservos; i++) { 54 pwm.setPWM(servos[i].channel, 0, servos[i].open); 55 } 56 } 57 58 59 void closeHand() { 60 for ( int i = 0; i < nservos; i++) { 61 pwm.setPWM(servos[i].channel, 0, servos[i].close); 62 } 63 }
65 66 Bibliography
[1] Sahab Babaee, Jongmin Shim, James C. Weaver, Elizabeth R. Chen, Nikita Patel, and Katia Bertoldi. 3D Soft Metamaterials with Negative Poisson’s Ratio. Advanced Materials, 25(36):5044–5049, September 2013.
[2] Yoseph Bar-Cohen, editor. Electroactive Polymer (EAP) Actuators as Artificial Muscles: Reality, Potential, and Challenges. SPIE Press, Bellingham, Wash, 2nd ed edition, 2004.
[3] Ray H Baughman, Justin M Shacklette, Anvar A Zakhidov, and Sven Stafström. Negative poisson’s ratios as a common feature of cubic metals. Nature, 392(6674):362–365, 1998.
[4] Ciprian Borcea and Ileana Streinu. Geometric auxetics. In Proc. R. Soc. A, volume 471. The Royal Society, 2015.
[5] Alexander S Boxerbaum, Kendrick M Shaw, Hillel J Chiel, and Roger D Quinn. Continuous wave peristaltic motion in a robot. The international journal of Robotics Research, 31(3):302–318, 2012.
[6] Eric Brown, Nicholas Rodenberg, John Amend, Annan Mozeika, Erik Steltz, Mitchell R. Zakin, Hod Lipson, and Heinrich M. Jaeger. Universal robotic gripper based on the jamming of granular material. Proceedings of the National Academy of Sciences, 107(44):18809–18814, November 2010.
[7] Berk Calli, Arjun Singh, James Bruce, Aaron Walsman, Kurt Konolige, Sid- dhartha Srinivasa, Pieter Abbeel, and Aaron M Dollar. Yale-CMU-Berkeley dataset for robotic manipulation research. The International Journal of Robotics Research, 36(3):261–268, March 2017.
[8] Yunteng Cao, Yilun Liu, Youlong Chen, Liangliang Zhu, Yuan Yan, and Xi Chen. A novel slithering locomotion mechanism for a snake-like soft robot. Journal of the Mechanics and Physics of Solids, 99:304–320, February 2017.
[9] L. Chin, J. Lipton, R. MacCurdy, J. Romanishin, C. Sharma, and D. Rus. Com- pliant electric actuators based on handed shearing auxetics. In 2018 IEEE In- ternational Conference on Soft Robotics (RoboSoft), pages 100–107, April 2018.
67 [10] Lillian Chin, Jeffrey Lipton, Michelle C. Yuen, Rebecca Kramer-Bottiglio, and Daniela Rus. Automated recycling separation enabled by soft robotic material classification. IEEE International Conference on Soft Robotics (RoboSoft) (In Press), IEEE, 2019.
[11] Lillian Chin, Michelle C. Yuen, Jeffrey Lipton, Luis H. Trueba, Rebecca Kramer- Bottiglio, and Daniela Rus. A simple electric soft robotic gripper with high- deformation haptic feedback. International Conference on Robotics and Au- tomation (In Press), IEEE, 2019.
[12] Raphael Deimel and Oliver Brock. A novel type of compliant and underactu- ated robotic hand for dexterous grasping. The International Journal of Robotics Research, 35(1-3):161–185, January 2016.
[13] A. Firouzeh and J. Paik. Grasp Mode and Compliance Control of an Underac- tuated Origami Gripper Using Adjustable Stiffness Joints. IEEE/ASME Trans- actions on Mechatronics, 22(5):2165–2173, October 2017.
[14] Kevin C Galloway, Panagiotis Polygerinos, Conor J Walsh, and Robert J Wood. Mechanically programmable bend radius for fiber-reinforced soft actuators. In Advanced Robotics (ICAR), 2013 16th International Conference on, pages 1–6. IEEE, 2013.
[15] Joseph N Grima, Elaine Chetcuti, Elaine Manicaro, Daphne Attard, Matthew Camilleri, Ruben Gatt, and Kenneth E Evans. On the auxetic properties of generic rotating rigid triangles. In Proc. R. Soc. A, page rspa20110273. The Royal Society, 2011.
[16] Joseph N Grima, Pierre-Sandre Farrugia, Ruben Gatt, and Daphne Attard. On the auxetic properties of rotating rhombi and parallelograms: a preliminary in- vestigation. physica status solidi (b), 245(3):521–529, 2008.
[17] Elliot W Hawkes, Eric V Eason, David L Christensen, and Mark R Cutkosky. Human climbing with efficiently scaled gecko-inspired dry adhesives. Journal of The Royal Society Interface, 12(102):20140675, 2015.
[18] B. S. Homberg, R. K. Katzschmann, M. R. Dogar, and D. Rus. Haptic iden- tification of objects using a modular soft robotic gripper. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1698– 1705, September 2015.
[19] Josie Hughes, Utku Culha, Fabio Giardina, Fabian Guenther, Andre Rosendo, and Fumiya Iida. Soft Manipulators and Grippers: A Review. Frontiers in Robotics and AI, 3, November 2016.
[20] Filip Ilievski, Aaron D. Mazzeo, Robert F. Shepherd, Xin Chen, and George M. Whitesides. Soft Robotics for Chemists. Angewandte Chemie, 123(8):1930–1935, February 2011.
68 [21] T. J. Wallin, J. H. Pikul, S. Bodkhe, B. N. Peele, B. C. Mac Murray, D. Therri- ault, B. W. McEnerney, R. P. Dillon, E. P. Giannelis, and R. F. Shepherd. Click chemistry stereolithography for soft robots that self-heal. Journal of Materials Chemistry B, 5(31):6249–6255, 2017.
[22] Robert K. Katzschmann, Andrew D. Marchese, and Daniela Rus. Hydraulic autonomous soft robotic fish for 3D swimming. In Experimental Robotics, pages 405–420. Springer, 2016.
[23] Kwang J Kim and Satoshi Tadokoro. Electroactive polymers for robotic appli- cations. Artificial Muscles and Sensors, 23:291, 2007.
[24] Sangbae Kim, Cecilia Laschi, and Barry Trimmer. Soft robotics: A bioinspired evolution in robotics. Trends in Biotechnology, 31(5):287–294, May 2013.
[25] Roderic Lakes. Foam structures with a negative poisson’s ratio. Science, 235:1038–1041, 1987.
[26] Cecilia Laschi, Barbara Mazzolai, and Matteo Cianchetti. Soft robotics: Tech- nologies and systems pushing the boundaries of robot abilities. Science Robotics, 1(1):eaah3690, December 2016.
[27] Arnaud Lazarus and Pedro M. Reis. Soft Actuation of Structured Cylinders through Auxetic Behavior. Advanced Engineering Materials, 17(6):815–820, 2015.
[28] Shuguang Li, Daniel M. Vogt, Daniela Rus, and Robert J. Wood. Fluid-driven origami-inspired artificial muscles. PNAS, page 201713450, November 2017.
[29] Huai-Ti Lin, Gary G. Leisk, and Barry Trimmer. GoQBot: A caterpillar-inspired soft-bodied rolling robot. Bioinspiration & Biomimetics, 6(2):026007, April 2011.
[30] Jeffrey Ian Lipton, Robert MacCurdy, Zachary Manchester, Lillian Chin, Daniel Cellucci, and Daniela Rus. Handedness in shearing auxetics creates rigid and compliant structures. Science, 360(6389):632–635, May 2018.
[31] Z-W Luo and Masami Ito. Control design of robot for compliant manipulation on dynamic environments. IEEE Transactions on Robotics and Automation, 9(3):286–296, 1993.
[32] Raymond Ma and Aaron Dollar. Yale OpenHand Project: Optimizing Open- Source Hand Designs for Ease of Fabrication and Adoption. IEEE Robotics & Automation Magazine, 24(1):32–40, March 2017.
[33] Robert MacCurdy, Robert Katzschmann, Youbin Kim, and Daniela Rus. Print- able hydraulics: A method for fabricating robots by 3D co-printing solids and liquids. In Robotics and Automation (ICRA), 2016 IEEE International Confer- ence On, pages 3878–3885. IEEE, 2016.
69 [34] Andrew D. Marchese, Robert K. Katzschmann, and Daniela Rus. A Recipe for Soft Fluidic Elastomer Robots. Soft Robotics, 2(1):7–25, March 2015.
[35] Andrew D. Marchese, Cagdas D. Onal, and Daniela Rus. Soft robot actuators using energy-efficient valves controlled by electropermanent magnets. In Intelli- gent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference On, pages 756–761. IEEE, 2011.
[36] Andrew G. Mark, Stefano Palagi, Tian Qiu, and Peer Fischer. Auxetic meta- material simplifies soft robot design. In 2016 IEEE International Conference on Robotics and Automation (ICRA), pages 4951–4956, Stockholm, Sweden, May 2016. IEEE.
[37] B Mazzolai, L Margheri, M Cianchetti, P Dario, and C Laschi. Soft-robotic arm inspired by the octopus: II. From artificial requirements to innovative techno- logical solutions. Bioinspiration & Biomimetics, 7(2):025005, June 2012.
[38] Aslan Miriyev, Kenneth Stack, and Hod Lipson. Soft material for soft actuators. Nature Communications, 8(1):596, September 2017.
[39] M. J. Mirzaali, S. Janbaz, M. Strano, L. Vergani, and A. A. Zadpoor. Shape- matching soft mechanical metamaterials. Scientific Reports, 8(1):965, January 2018.
[40] Bobak Mosadegh, Panagiotis Polygerinos, Christoph Keplinger, Sophia Wennst- edt, Robert F Shepherd, Unmukt Gupta, Jongmin Shim, Katia Bertoldi, Conor J Walsh, and George M Whitesides. Pneumatic networks for soft robotics that ac- tuate rapidly. Advanced Functional Materials, 24(15):2163–2170, 2014.
[41] Lael U. Odhner, Leif P. Jentoft, Mark R. Claffee, Nicholas Corson, Yaroslav Tenzer, Raymond R. Ma, Martin Buehler, Robert Kohout, Robert D. Howe, and Aaron M. Dollar. A compliant, underactuated hand for robust manipulation. The International Journal of Robotics Research, 33(5):736–752, April 2014.
[42] Daniel Paluska and Hugh Herr. The effect of series elasticity on actuator power and work output: Implications for robotic and prosthetic joint design. Robotics and Autonomous Systems, 54(8):667–673, August 2006.
[43] Kirstin H. Petersen and Robert F. Shepherd. Fluid-driven intrinsically soft robots. In Robotic Systems and Autonomous Platforms, pages 61–84. Elsevier, 2019.
[44] Panagiotis Polygerinos, Nikolaus Correll, Stephen A. Morin, Bobak Mosadegh, Cagdas D. Onal, Kirstin Petersen, Matteo Cianchetti, Michael T. Tolley, and Robert F. Shepherd. Soft Robotics: Review of Fluid-Driven Intrinsically Soft Devices; Manufacturing, Sensing, Control, and Applications in Human-Robot Interaction. Advanced Engineering Materials, 19(12), December 2017.
70 [45] G. A. Pratt and M. M. Williamson. Series elastic actuators. In Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots, volume 1, pages 399–406 vol.1, August 1995.
[46] Ahmad Rafsanjani, Katia Bertoldi, and André R. Studart. Programming soft robots with flexible mechanical metamaterials. Science Robotics, 4(29):eaav7874, April 2019.
[47] Steven I. Rich, Robert J. Wood, and Carmel Majidi. Untethered soft robotics. Nature Electronics, 1(2):102–112, February 2018.
[48] Matthew A. Robertson and Jamie Paik. New soft robots really suck: Vacuum- powered systems empower diverse capabilities. Science Robotics, 2(9):eaan6357, August 2017.
[49] Daniela Rus and Michael T Tolley. Design, fabrication and control of soft robots. Nature, 521(7553):467, 2015.
[50] FranÃğois Schmitt, Olivier Piccin, Laurent BarbÃľ, and Bernard Bayle. Soft robots manufacturing: A review. Frontiers in Robotics and AI, 5:84, 2018.
[51] Audrey Sedal, Michael Fisher, Joshua Bishop-Moser, Alan Wineman, and Srid- har Kota. Auxetic Sleeves for Soft Actuators with Kinematically Varied Surfaces. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 464–471, Madrid, October 2018. IEEE.
[52] Jianhu Shen, Shiwei Zhou, Xiaodong Huang, and Yi Min Xie. Simple cubic three- dimensional auxetic metamaterials. physica status solidi (b), 251(8):1515–1522, August 2014.
[53] Robert F. Shepherd, Adam A. Stokes, Rui M. D. Nunes, and George M. White- sides. Soft Machines That are Resistant to Puncture and That Self Seal. Advanced Materials, 25(46):6709–6713, December 2013.
[54] Samuel Shian, Katia Bertoldi, and David R. Clarke. Dielectric Elastomer Based “Grippers” for Soft Robotics. Advanced Materials, 27(43):6814–6819, November 2015.
[55] Jun Shintake, Vito Cacucciolo, Dario Floreano, and Herbert Shea. Soft robotic grippers. Advanced Materials, page 1707035, 2018.
[56] Michael T. Tolley, Robert F. Shepherd, Bobak Mosadegh, Kevin C. Galloway, Michael Wehner, Michael Karpelson, Robert J. Wood, and George M. White- sides. A Resilient, Untethered Soft Robot. Soft Robotics, 1(3):213–223, August 2014.
71 [57] A Villoslada, A Flores, D Copaci, D Blanco, and L Moreno. High-displacement flexible shape memory alloy actuator for soft wearable robots. Robotics and Autonomous Systems, 73:91–101, 2015.
[58] Gordon G. Wallace, Peter R. Teasdale, Geoffrey M. Spinks, and Leon A. P. Kane- Maguire. Conductive Electroactive Polymers: Intelligent Polymer Systems, Third Edition. CRC Press, October 2008.
[59] Amir Yeganeh-Haeri, Donald J Weidner, and John B Parise. Elasticity of 훼-cristobalite: A silicon dioxide with a negative poisson’s ratio. Science, 257(5070):650–652, 1992.
[60] Xuance Zhou, Carmel Majidi, and Oliver M. O’Reilly. Soft hands: An analysis of some gripping mechanisms in soft robot design. International Journal of Solids and Structures, 64-65:155–165, July 2015.
72