Original Research
published: 26 September 2017
doi: 10.3389/frobt.2017.00046

A
Jiawei Zhang1, Andrew Jackson2,3, Nathan Mentzer 2,3 and Rebecca Kramer1,4*
1
School of Mechanical Engineering, Purdue University, West Lafayette, IN, United States, 2 Polytechnic Institute, Purdue
University, West Lafayette, IN, United States, 3 College of Education, Purdue University, West Lafayette, IN, United States,
4
Department of Mechanical Engineering and Materials Science, Yale University, New Haven, CT, United States

Edited by:
Matteo Cianchetti,Sant’Anna School of Advanced
Studies, Italy
Reviewed by:Gursel ALICI,
University of Wollongong, Australia
Ali Sadeghi,
Fondazione Istituto Italiano diTechnologia, Italy*Correspondence:
Rebecca Kramer
rebecca.kramer@yale.edu
Specialty section:
This article was submitted toSoft Robotics,
a section of the journal
Frontiers in Robotics and AI
Received: 27 June 2017
Accepted: 04 September 2017
Published: 26 September 2017
Citation:Zhang J, Jackson A, Mentzer N and
Kramer R (2017) A Modular,
Reconfigurable Mold for a Soft
Robotic Gripper Design Activity.
Front. Robot. AI 4:46.
doi: 10.3389/frobt.2017.00046

Soft robotics is an emerging field with strong potential to serve as an educational tool
due to its advantages such as low costs and shallow learning curves. In this paper,
we introduce a modular and reconfigurable mold for flexible design of pneumatic soft
robotic grippers. By using simple assembly kits, students at all levels are able to designand construct soft robotic grippers that vary in function and performance. The processof constructing the modular mold enables students to understand how design choices
impact system performance. Our unique modular mold allows students to select the
number and length of fingers in a gripper, as well as to adjust the internal geometry of
the pneumatic actuator cavity, which dictates how and where bending of a finger occurs.
In addition, the mold may be deconstructed and reconfigured, which allows for fast
iterative design and lowers material costs (since a new mold does not need to be madeto implement a design change). We further demonstrate the feasibility of the modular
mold by implementing it in a soft robot design activity in classrooms and showing asufficiently high rate of student success in designing and constructing a functional soft
robotic gripper.
Keywords: soft robotics, gripper, design, engineering education, modular

1. INTRODUCTION
Robotics has been demonstrated as an effective vehicle for hands-on learning of technical andtinkering skills (Hamner et al., 2008; Desai et al., 2009; Adamchuk et al., 2012). As such, robotics
is being rapidly integrated into K-12 education and extracurricular activities, where the education
objectives include lessons in mechanics, electronics, programming, problem-solving, and design
thinking (McGrath et al., 2008). While there are a host of educational robotics tools, such as
Arduino, LEGO Mindstorms, Fischertechniks, and crowd-funded robotics startups emerging on
Kickstarter, perhaps the most widespread implementation of educational robotics is through U.S.
FIRST (For Inspiration and Recognition of Science and Technology), which includes a competition
for high-school students to challenge their ability to design and build a full-scale functional robot.
However, these existing approaches do little to expose the next generation to emerging fields ofrobotics, such as soft robotics.
Our goal in this work is to enable a soft robot design activity that retains the learning outcomesof more traditional robot design activities, but reduces the time, cost, and complexity of implementation. Traditional robotics requires elements such as motors, gears, wires, and computer codes.
By contrast, soft robots are constructed from elastomeric polymers, actuated by material deformationand tend to have a more “organic” feel and appearance that can remind students of animals andobjects seen in nature. These elements are more closely related to the disciplines of materials science,

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Modular Mold for Gripper Design

biology, and chemistry instead of traditional engineering disciplines. Soft robots are also mechanically robust and inherently
safe for humans to interact with (Laschi and Cianchetti, 2014;
Abidi and Cianchetti, 2017), as well as more affordable whencompared to most traditional robots (Polygerinos et al., 2015;
Della Santina et al., 2017). By shifting the fundamental building
blocks and leveraging the advantages of soft robotics, we believe
there may be an opportunity to broaden interest in robotics and
STEM disciplines among K-12 students.
In this work, we focus on using a modular, reconfigurable
mold as the foundation of a soft robot design activity in an
entry-level STEM course. While pneumatic soft robotics is anactive and complex field of research, the basic concept of fillinga balloon-like structure with air to make it move is quite simple.
As such, at least one soft robotics activity has been developed
and tested with a variety of age groups, ranging from elementaryschool students to high-school students (Finio et al., 2013). The
activity adopts the same fabrication process as we do, but it does
not allow students to make any modifications to the mold, andfocuses on building rather than design. Our approach of using
modular, reconfigurable molds uses the same basic materials andconcept, while enabling students to change the configuration of
the resulting robot.
The concept of modular soft robotics has been demonstrated
previously, but only in a laboratory context. Specific examples
include modular soft robotic components attached throughmagnetic connections (Kwok et al., 2014) or mechanical connectors (Onal and Rus, 2012; Ranzani et al., 2013). Although thesemethods provide a reasonable amount of design freedom duringassembly, they involve pre-fabricated soft pneumatic modules
and may not provide students with the opportunity to construct
soft robots from scratch. Rather than focusing on modular
components, in this work, we build upon the existing activity byintroducing a modular mold that allows students to participate in
the design of non-modular soft grippers. Figure 1 demonstrates
the reconfigurability of the mold and also shows an example

gripper fabricated with the modular mold gripping a variety ofobjects. In the rest of this paper, we describe the developmentof the modular mold, the classroom context for implementation,and the testing criteria and results.

2. MOLD DESIGN
Throughout the development of the modular mold, we sought tooptimize two metrics: design freedom and success rate. Design
freedom allows students to investigate variables that govern the
behavior of a system, create a design to optimize performance,
and then build, test, and improve the design (International
Technology Education Association and Technology for All
Americans Project, 2007). By providing multiple degrees ofdesign freedom, we encourage students to explore and be creative, which enables learning outcomes in both design and fabrication—students learn not only how to make soft robots, but also
how to design soft robots.
In addition, success rate during implementation is criticalfor student self-confidence and continued interest in engineering learning (Bandura, 1977, 2006; Britner and Pajares, 2006;
Mamaril et al., 2016). Through our preliminary work, we haveobserved that even a robot that might be considered a “failure” bylaboratory standards typically resulted in an organic, “squirmy”
motion that students naturally find intriguing. While obtaining asufficiently high success rate is a focus of the modular mold evaluation, the soft robot design experience also provides a context
to emphasize building and iteration. Considering the context
of robotics education, our goal is not to eliminate these failuremodes, but rather to help students identify the cause and effect offailures, thus enabling the iterative design experience needed andguide students to turn ideas into principles of practice (Kolodneret al., 1998).
While both design freedom and success rate are important,previous mold designs excel in one or the other, but not both
(Section A in Supplementary Material). Therefore, our goal in

Figure 1 | The modular mold kit and a sample soft gripper made from this mold. (A,B) The mold pieces are reconfigurable and many variations of the mold can bebuilt using the same parts; (C) completely assembled mold; (D) top view of the gripper; (E) bottom view of the gripper; (F) picking up a golf ball; (G) picking up abox of candy; (H) picking up a computer mouse; (I) picking up a glue bottle; (J) picking up a roll of tape.

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this work was to increase both metrics in parallel by developing a
modular mold. The resulting modular mold comprises six typesof mold parts, as shown in Figure 2, but the combination of theseparts can result in numerous actuation patterns and behaviors,
giving students the opportunity to learn and practice engineering
design through iterations. The modular mold kit allows students
to select the number of fingers for their gripper design, the number and placement of pneumatic cavities in each finger, and thethickness of the gripper.
The choice of the number of gripper fingers allows students
to familiarize themselves with how to make soft robots by
experimenting with a single finger before taking on the moredifficult task of making an entire soft gripper. Making single soft
pneumatic fingers of various designs also provides feedback
regarding the success of the designs, which students can thenemploy to design a full multi-fingered gripper. Furthermore,even in the design of the full gripper, students may vary the
number of fingers, thus customizing the gripper to effectively manipulate target objects of specific shapes, sizes, andweights.
An additional highlight of our mold design is the reconfigurable pneumatic networks (often referred to as pneunets in theliterature (Ilievski et al., 2011)), which allow curvature of thepneumatic fingers to be designed, as shown in Figure 3. Whileprevious molds have featured static pneumatic networks, we haveintroduced clips and ridges (Figure 2B) where the clips can bepress-fitted to any location on a ridge and may be easily removed
and reconfigured. Both the clips and ridges combine to form airchambers in the resulting finger/gripper that define inflation andactuation of the system.
Finally, students may change the thickness of the finger/
gripper by varying the amount of polymer poured into the mold,which will cause more or less bending given a specific pressure.
Taken as a whole and compared with previous mold designs, ourmodular mold provides much more design freedom and flexibility, as summarized in Table 1.

3. IMPLEMENTATION
To test the performance of the modular mold, we implemented
a soft robotics design activity through a design curriculum infour high-school classrooms, similar to some outreach activities that we had run in the past, as seen in Figure 4. The curriculum was contextualized in a course for 9th-grade students

Figure 2 | Components of the modular mold and its application in the soft robotic gripper design activity. (A) The mold has six different parts, including a hub, end
caps, finger caps, middle pieces, a coupler, and clips; (B) an exploded view that shows how the mold is assembled; (C) the eight-step fabrication process of a soft
robotic gripper using the modular mold kit; (i) prepare materials; (ii) assemble mold; (iii) prepare silicone elastomer mixture; (iv) pour silicone elastomer into mold and
let it cure; (v) remove cured rubber from mold; (vi) apply fabric and attach coupler, let them cure; (vii) trim off extra fabric; (viii) inflate.

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Figure 3 | Demonstration of the modular mold’s design freedom. On the left are the sample mold configurations, and on the right are the respective finished soft
fingers and grippers. (A) A single large pneumatic chamber created by placing four clips together; (B) two sets of clips that are slightly spaced apart; (C) three setsof “double clips” (two clips set next to each other); (D) five evenly spaced clips; (E) three-fingered gripper with equal finger length; (F) four-fingered gripper withdifferent finger length.

Table 1 | Degrees of design freedom offered by the modular mold kit.
Design freedom

Choices

Robot type
Number of fingers
Finger length
Clips
Top layer thickness

Finger, gripper
3 or 4
0–3 mid pieces
Quantity, spacing
Variable

Examples (Figure 3)
A–D vs E,F
E vs FF
A–D
A–F

called Foundations of Technology, which is delivered nationallyby the STEM Center for Teaching and Learning, a branchof the International Technology and Engineering Educators
Association (ITEEA). We note that the work presented herein
is part of a larger study aimed at measuring differences in engineering motivation and self-efficacy of students after engaging
in either a soft robot design experience or a traditional robot
design experience. Development of the modular mold and themeasurement of corresponding success rate are foundational tothis larger study, as initial success is critical for self-confidence
and continued interest in engineering learning (Bandura, 1977,
2006; Britner and Pajares, 2006; Mamaril et al., 2016).
The implementation took about 8 h to complete over multiple
90-min class sessions. During this time, students designed andfabricated two fingers that varied in design in order to test the

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Figure 4 | Students participating in the soft robotic gripper design activity
at Purdue’s Innovation to Reality (I2R) event. Written and informed consent
has been obtained from the parents/legal guardians of all depicted individuals
for the publication of their children’s identifiable images.

impact of variables on finger curvature and performance, thenleveraged their findings to design and fabricate a full multifingered soft robotic gripper for the specified task of grasping

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Modular Mold for Gripper Designand holding a golf ball for at least 5 s. The majority of students
completed the implementation in groups of two, although there
were a few groups of three and some students who worked
independently, with about 10–15 groups in each classroom. The
implementations were administered by the course teachers, who
had attended a professional development meeting prior to theimplementations to receive training for the soft robot design
activity. Example activity instructions, as well as curriculum
materials including a soft robotic gripper design brief and process
overview, are provided in the Sections B–D in Supplementary
Material.

and air leaking due to failed seals. Clogging was usually caused
by applying an excessive amount of silicone elastomer on the
fabric, which would clog the pneumatic actuator cavities, or air
channels. Air leaks were usually caused by not applying enoughliquid silicone elastomer around the cured silicone elastomer
or on the fabric, leaving holes that prevent the grippers frominflating. Another observed failure mode was elastomer rupture,
which could be caused by either a non-level curing surface orinsufficient filling of the mold. In addition, air bubbles were occasionally identified on the top surface of the gripper, which also
contributes to elastomer rupture. Possible causes include mixing
the silicone elastomer too vigorously and/or not allowing thesilicone elastomer to degas before curing it in the oven. Finally,some cases of failure were a result of overheated molds: as themolds are made of 3D printed thermoplastic, heating the moldnear or above the glass transition temperature caused significant
mold warping.
We note that all of the above failure modes, accounting for
81% of all observed failures, are process-related and would have
happened for a non-modular mold as well. Only a single failuremode was observed that was related to modularizing the mold.
This mold-related failure mode was a result of clips insufficiently
connecting to the mold ridges, which in turn caused the clips
to detach from the ridges when filling the mold with elastomer.
Based on the failure mode data we collected (Table 2), we inferthat the modular design had a minimum effect on the successrate. Furthermore, since our gripper inspection was performed
after student testing and presentations, some grippers had alreadyfailed when we handled them. It is possible that they worked
at one point but ruptured later when students overinflated or
performed destructive testing on their grippers. Therefore, thesuccess rate presented here is conservative.

4. RESULTS
Success rate for the activity was evaluated via direct inspection
and testing of the student-fabricated grippers by our researchteam, as well as interviews with participating students and teachers. Success was defined by completion of the design task: if agripper could grasp and hold a golf ball for 5 s, it was deemed
successful. We inspected and evaluated a total of 54 grippers
resulting from the classroom implementations. Overall, 29 out of
the 54 grippers were successful (a success rate of 54%), while 25
were unsuccessful. Among the successful grippers, we observedthat students utilized the design freedom of the modular moldby adjusting the lengths of fingers, the number of clips inserted,and the spacing between the clips (Figures 5A–D). In addition,
multiple teams demonstrated successful grippers by picking up
the golf ball and holding it for 5 s (Figures 5E–H). Thus, themodular mold produced positive results in both design freedom
and success rate.
However, we also observed some failed grippers, as shown in
Figure 6. The two most common failure modes were clogging

Figure 5 | Successful fingers and grippers designed and fabricated by students. (A) Multiple assembled finger molds with different length and different number
and spacing of the clips; (B) an assembled gripper mold with different finger lengths and different numbers of clips; (C) a successful soft finger with three airchambers; (D) a successful gripper fabricated by the students without any clips; (E–H) various grippers demonstrating the ability to pick up the golf ball and hold it
for 5 s.

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Figure 6 | Common failure modes from the classroom implementations and some of students’ attempts to repair the grippers. (A) Air leaking from a hole causedby floating clips; (B) air leaking from the side; (C) air leaking from an air bubble; (D) center of the robot was inflated due to multiple clogged air channels; (E) a few
warped molds; (F) the warped molds bending upward; (G) students tried to fix an air leaking by tying a rubber band around it; (H) students attached a finger to thegripper instead of using the coupler.

On the other hand, we question whether the success rateachieved was sufficiently high in these initial implementation
attempts with the modular mold. Students’ achieved success plays
an important role in affecting student attitudes and is critical toreaching our broader goal of enhancing student self-efficacy,
motivation, and subsequent STEM interest through soft robot
design experiences. Although the success rate varied from class
to class, the four classes that implemented the soft robot design
curriculum achieved an overall success rate of 54%. Currently,
there is no documented success rate for the previous soft robot
gripper activity and, as a result, we are not in a position to draw
comparisons. Instead, in order to make conclusions, we situate
this success rate in relation to motivational theory (Vygotsky,1987) and measured student outcomes (self-efficacy) that we havepreviously reported (Jackson et al., 2017).
Vygotsky (1987) introduced the concept of The Zone of
Proximal Development (ZPD), which we describe to situate ourfindings. This theory describes that when a student is within the
ZPD for a particular task, providing the appropriate assistance(scaffolding) will enhance the student’s abilities enough to successfully complete the task. An appropriately situated instructional
task will be challenging enough that it stretches the students, yet
includes the necessary resources for them to accomplish the task.
In our case, the teachers’ instructions, handouts, and processdemonstrations (Sections B–D in Supplementary Material) seem
to provide this support. Since we have not received any feedback
that the activity was too challenging or too straightforward, we
argue that we are indeed within the ZPD and that completing suchan activity can serve to enhance student abilities (Yorke, 2003).
Further evidence of appropriate challenge in the activity isbased on measured outcomes of the activity (Jackson et al., 2017).
As part of our broader study, pre- and post-surveys were conducted for both the soft robot design activity described herein

Table 2 | Failure mode statistics of the soft robotic grippers.
Failure mode
Air leaking due to failed seals
Clogging
Thin top layer due to unlevel curing surface ormold warping
Air leaking due to floating clips
Air leaking due to air bubbles on top layer
Total

Quantity

Percent

Cause

15
7
3

55
26
11

Process
Process
Process

1
1
27

4
4
100

Mold
Process

Note that two of the 25 failed grippers demonstrated dual failure modes. Therefore, thetotal number of failures is 27 instead of 25.

5. DISCUSSION
The intent of this research was to produce and test a modular moldfor soft robotic fabrication that increased design freedom while
maintaining a sufficiently high success rate. On the one hand,classroom observation and gripper inspection indicated thatstudents were indeed using the modularity and design featuresof the mold pieces to change their designs. For example, studentschanged the number and spacing of clips and also adjusted thelength of the fingers to pick up the specified objects. During
the fabrication process, filled lines in the mold helped students
control the amount of silicone elastomer and ensured that theirmold was curing on a level surface. The reusability of the modular
finger and gripper mold pieces allowed students to apply theirlearning from design and fabrication of fingers to the design andfabrication of full multi-fingered grippers. Finally, the modular
mold was quick to assemble and, as a result, students were able
to focus on design iterations. Compared to the one-piece mold(Finio et al., 2013), the modular mold has evidently expanded
design freedom.

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and a traditional robot design activity with identical learning outcomes. Preliminary survey scores were collected and analyzed tosee if there was a change in students’ levels of self-efficacy before
and after the activity, as well as differences between the types ofrobotics activity. Based on ANOVA results reported in our otherwork (Jackson et al., 2017), there was a statistically significant difference in the self-efficacy change over time between the types ofrobotics activity (p = 0.03, η2 = 0.025): the mean self-efficacy fromthe traditional robotics activity decreased (ΔMH = − 0.1), while
the mean self-efficacy from the soft robotic gripper design activity
increased (ΔMS = 0.2). While the practical significance is small,the results are still promising for future iterations. The statisticallysignificant change in self-efficacy supports our conclusion thatthe modular design is meeting the education objectives because
the success rate is sufficiently high to foster students’ confidence.
When approached carefully, student experiences with design
failure can provoke meaningful discussion and learning opportunities (Lottero-Perdue and Parry, 2017). We hope that further
changes to the curriculum materials that improve the overall
success rate will magnify the effects on student self-efficacy which
we have observed.

the modular mold and the curriculum. We will also continue toresearch the efficacy of the experience as we collect more successrate data. This is the first time that soft robotics has been formally
introduced into STEM education, and we believe that this work
will be instrumental in advancing current and future robotics
programs.

ETHICS STATEMENT
This study was carried out in accordance with the recommendations of the Purdue University institutional review board.
Written and informed consent has been obtained from all adultparticipants and from the parents/legal guardians of all nonadult participants. The study and the protocol were reviewed andapproved by the Purdue University institutional review board.

AUTHOR CONTRIBUTIONSRK and NM conceived and designed the research. All authors
contributed to the acquisition, analysis, and interpretation ofdata for the work. JZ and RK wrote the manuscript with critical
input from AJ and NM. All authors agreed to be accountable for
all aspects of the work in ensuring that questions related to theaccuracy or integrity of any part of the work are appropriately
investigated and resolved.

6. CONCLUSION
In this work, we have introduced a modular, reconfigurable
mold kit for a soft robotic gripper design activity. We also
demonstrated the feasibility of a soft robotics program using thismodular mold by showing results from classroom implementations. By breaking down the mold design and giving users the
freedom to control several key design parameters, we provide
users with a unique design learning experience. Our modular
mold kit design also produced a sufficiently high success ratethat enabled students to achieve the desired learning outcomes.
Furthermore, we have identified common failure modes during
fabrication of the soft robotic grippers made from the modular
mold kit and provided recommendations to assist users in theiterative design process.
During our school visits, we observed that students were
engaged throughout the activity and that the overall experience
was positive. Participants also indicated that they were likely torecommend this activity to other fellow students because of theunique, organic characteristics of soft robotics, which differentiates this activity significantly from existing robotics programs.
Data collection in the form of feedback and assessments fromboth teachers and students will further evaluate the reliability of
our modular mold to improve learning outcomes such as selfefficacy and motivation for STEM disciplines. We are currently
preparing for the second round of classroom implementations,and we expect the success rate to increase as we continue to refine

ACKNOWLEDGMENTS
We would like to thank R. Adam Bilodeau, a Ph.D. student in the
Purdue Faboratory, for his contribution to this work. We would
also like to acknowledge the efforts made by Sarah Hacker, anundergraduate student from Purdue University, and Shae Henry,
an undergraduate student from Georgetown College. Sarah
Hacker generated multiple mold design concepts and contributed
to the early stage development of this work, while Shae Henry
spent a summer in the Purdue Faboratory continuing to improvethe mold design and also creating a demonstration video thathelps first-time users to learn how to make soft grippers.

FUNDING
This work was supported by the National Science Foundation
under Grant DRL-1513175.

SUPPLEMENTARY MATERIALThe Supplementary Material for this article can be found online at
http://journal.frontiersin.org/article/10.3389/frobt.2017.00046/
full#supplementary-material.

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Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could beconstrued as a potential conflict of interest.
Copyright © 2017 Zhang, Jackson, Mentzer and Kramer. This is an open-access article
distributed under the terms of the Creative Commons Attribution License (CC BY).
The use, distribution or reproduction in other forums is permitted, provided theoriginal author(s) or licensor are credited and that the original publication in thisjournal is cited, in accordance with accepted academic practice. No use, distribution
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September 2017 | Volume 4 | Article 46