Revista de Ciencias Tecnológicas (RECIT). Volumen 3 (1): 10-22
Revista de Ciencias Tecnológicas (RECIT). Universidad Autónoma de Baja California ISSN 2594-1925
Volumen 9 (3): e502. Julio-Septiembre, 2026. https://doi.org/10.37636/recit.v9n3e502
ISSN: 2594-1925
1
Research article
Design, fabrication and experimental evaluation of a three-
finger Fin Ray soft gripper
Diseño, fabricación y evaluación experimental de una pinza blanda de tres
dedos tipo Fin Ray
Hoang Bui Huy
VNU University of Engineering and Technology, Vietnam National University, Hanoi, Vietnam. E-mail:
hoangbh86@vnu.edu.vn. ORCID: 0009-0002-3446-210X.
Received: July 8, 2026 Accepted: July 30, 2026 Published: August 8, 2026
Abstract.- This study presents the design, finite element analysis, fabrication, and experimental validation of a low-
cost three-finger soft gripper based on the Fin Ray effect. The proposed system integrates TPU 95A compliant
fingers, a PLA supporting structure, and an Arduino-controlled stepper-motor actuation mechanism. Several Fin
Ray rib configurations were systematically evaluated using analytical modelling, finite element simulations, and
experimental testing under a representative 5 N loading condition. The results showed that the contact region
located approximately between one-half and two-thirds of the finger length produced the most effective deformation
behavior. Among the investigated configurations, the curved-rib design achieved the largest displacement of
approximately 14.45 mm while maintaining stable grasping performance. Good agreement was obtained between
numerical predictions and experimental measurements, with deformation errors generally below 10% and a
maximum error of 11.22%. The study establishes a reproducible CAD–FEA–3D printing experimental validation
workflow and demonstrates a low-cost Fin Ray soft gripper platform that can support future research, rapid
prototyping, and engineering education.
Keywords: Soft gripper; Fin Ray effect; Additive manufacturing; TPU; Finite element simulation; Experimental
validation; Robotic grasping.
Resumen.- Este estudio presenta el diseño, el análisis por elementos finitos, la fabricación y la validación
experimental de una pinza blanda de tres dedos de bajo coste basada en el efecto Fin Ray. El sistema propuesto
integra dedos flexibles de TPU 95A, una estructura de soporte de PLA y un mecanismo de accionamiento mediante
motor paso a paso controlado por Arduino. Se evaluaron sistemáticamente varias configuraciones de nervaduras
Fin Ray utilizando modelos analíticos, simulaciones por elementos finitos y ensayos experimentales bajo una
condición de carga representativa de 5 N. Los resultados mostraron que la zona de contacto situada
aproximadamente entre la mitad y los dos tercios de la longitud del dedo producía el comportamiento de
deformación más eficaz. Entre las configuraciones estudiadas, el diseño con nervaduras curvas logró el mayor
desplazamiento —aproximadamente 14,45 mm— manteniendo al mismo tiempo un rendimiento de agarre estable.
Se obtuvo una buena concordancia entre las predicciones numéricas y las mediciones experimentales, con errores
de deformación generalmente inferiores al 10 % y un error máximo del 11,22 %. El estudio establece un flujo de
trabajo reproducible de validación experimental (CAD-FEA-impresión 3D) y demuestra la viabilidad de una
plataforma de pinza blanda Fin Ray de bajo coste que puede servir de apoyo para futuras investigaciones, la
creación rápida de prototipos y la enseñanza de la ingeniería.
Palabras clave: Pinza blanda; Efecto Fin Ray; Fabricación aditiva; TPU; Simulación por elementos finitos; Validación
experimental; Agarre robótico.
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1. Introduction
Soft robotics has become an important research direction for robotic manipulation because compliant structures can
interact safely with uncertain environments and objects with variable shape, stiffness, and surface condition.
Compared with rigid end effectors, soft grippers distribute contact deformation over larger areas and reduce local
pressure, which is particularly relevant for food handling, agricultural manipulation, biomedical tools, and service
robots [1]-[5].
Within this field, the Fin Ray effect offers a simple passive mechanism for adaptive grasping. A ribbed triangular
finger bends toward the applied contact force rather than away from it, enabling the finger to wrap around curved
or irregular surfaces without requiring a fully articulated mechanism or complex sensing system. Previous studies
have demonstrated Fin Ray based soft grippers, 3D printed Fin Ray fingers, finite-element optimization, and
analytical modelling for compliant manipulation [6]-[10].
Recent research has also moved beyond empirical design toward data driven prediction, tactile integration, and
structural optimization of Fin Ray fingers. Physics informed neural networks, reconfigurable tactile grippers,
learning based finger design, and layer jamming Fin Ray fingers have been proposed to improve deformation
prediction, grasp stability, and task adaptability [11]-[14].
Additive manufacturing is closely related to this design direction because it allows fast iteration of rib geometry
and direct fabrication of compliant or semi compliant structures. Studies on soft matter printing, 3D printing of soft
robotic systems, soft robot manufacturing, and soft robotic materials show that material selection, process
anisotropy, and fabrication parameters strongly influence the final mechanical response of soft grippers [15]-[18].
Other soft robotic and compliant grasping approaches provide useful design principles for the present work.
Elastomeric soft systems, fiber reinforced bending actuators, fluidic elastomer robots, underactuated hands, and
granular jamming grippers show that mechanical compliance can reduce control complexity while maintaining
practical grasping capability [19]-[23].
Application oriented studies further indicate that soft grippers can be adapted for biomedical manipulation, stiffness
adjustable systems, general soft manipulators, and small-scale robotic actuation. These studies emphasize the need
to balance compliance, load capacity, repeatability, and safe interaction with fragile objects [24]-[27].
Recent work on self-healing soft robots, electroadhesive soft grippers, and comparative evaluations of soft-gripper
technologies also highlights the importance of durability, contact control, and application specific actuation
selection. These issues motivate the present low-cost Fin Ray gripper design and experimental validation workflow
[28]-[30].
Based on this background, the present paper develops a complete design-oriented case study using the data and
images obtained from the prototype thesis project. The main contributions are: (i) comparison of several ribbed Fin
Ray finger geometries; (ii) fabrication of a three finger TPU/PLA prototype using FDM; (iii) integration of an
Arduino-based stepper motor drive; and (iv) validation on objects with spherical, cylindrical, and fragile surfaces.
Beyond the development of a functional prototype, this study proposes a complete design workflow integrating
CAD modelling, finite element analysis, FDM-based fabrication, and experimental validation. It also compares
multiple Fin Ray rib configurations and incorporates analytical design equations to support geometry selection and
preliminary performance evaluation. The resulting low-cost platform is readily reproducible and provides a practical
basis for both soft-robotics research and engineering education.
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2. Design Methodology
The Fin Ray finger is composed of two flexible outer beams connected by a set of internal ribs. The outer boundary
is tapered toward the fingertip, forming a triangular or wedge like structure. When the object contacts one side of
the finger, the internal ribs redistribute deformation and cause the finger body to curve toward the object. This
passive geometric adaptation is suitable for grasping objects whose exact profile is not known in advance.
In this work, the finger design target is not maximum load capacity, but stable and gentle grasping. The finger must
therefore satisfy three design requirements: high enough compliance to follow the object surface, sufficient stiffness
to prevent slip, and sufficient fatigue resistance for repeated opening and closing cycles. The selected gripper
architecture uses three identical fingers equally distributed around the central body to improve centering and
increase the total contact area.
Figure 1. Fin Ray deformation principle used as the basis for the soft finger design.
Table 1. Main materials and functional components of the prototype.
Component
Material
Main role
Key properties used in design
Soft fingers
TPU 95A
Compliant deformation and
contact with object
Shore hardness 60-95A; density about 1230
kg/m3; tensile strength 22-55 MPa;
elongation at break about 450%
Main body
and links
PLA
Structural support and
mounting
Density about 1340 kg/m3; tensile strength
50-60 MPa; elastic modulus about 700 MPa;
melting point about 220 °C
Actuation
unit
Stepper motor +
lead-
screw/slider
linkage
Convert rotation to finger
closing motion
Nominal 1.8° step angle; low-cost position
control
Control unit
Arduino Uno +
A4988 driver
Pulse/direction control of the
stepper motor
Simple open loop actuation with adjustable
step count
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For a journal style design paper, the Fin Ray finger can be idealized as a tapered compliant structure with distributed
internal ribs. The local outer width is approximated by a linear taper, while the rib layout controls the equivalent
bending stiffness and the direction of passive deformation.
󰇛󰇜 󰇛󰇜
 (1)
where w(x) is the local finger width at distance x from the fixed base, wb and wt are the finger widths at the base
and at the tip, respectively, and L is the effective finger length. The contact location is then expressed in
dimensionless form as
󰇥
󰇦 (2)
where xc is the contact position measured from the fixed base and λ is the corresponding dimensionless contact
position. The simulation results in the original thesis show that the middle contact region, λ approximately 0.50-
0.67, gives the most effective deformation mode because it provides a large contact area without excessive local
distortion.

  
(3)
where keff is the effective stiffness of one finger, Ceff is the corresponding compliance, Fn is the normal force acting
on one finger, and δtip is the tip displacement. These indicators are useful for comparing different rib geometries
under the same nominal normal force.
(4)
where Fc is the total commanded or equivalent clamping force of the gripper and Fn is the normal force carried by
one finger. Equation (4) assumes that the three identical fingers share the clamping force uniformly, which is
appropriate for preliminary sizing and for symmetric objects placed near the centre of the gripper.
The baseline finger has a tapered external profile and internal ribs. The initial geometry was created in SolidWorks
and then modified to evaluate the effect of rib orientation and rib distribution. The numerical comparison used a 5
N lateral load applied at several positions along the finger surface. The finger base was fully fixed to reproduce the
actual mounting condition in the gripper body.
Three main contact locations were considered: near one-third of the finger length from the base, between one-half
and two-thirds of the finger length, and near the fingertip. The simulation results show that the middle contact region
provides the best compromise between bending deformation and mechanical stability. This region also corresponds
to the expected contact zone when the gripper surrounds objects such as fruit, bottles, or eggs.
To ensure a consistent comparison among different Fin Ray finger configurations, a representative 5 N normal load
was applied in all finite element simulations. This load corresponds to the typical grasping force required for
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lightweight household objects while remaining within the elastic deformation range of the TPU fingers. The three
loading positions were selected to represent contact near the finger base, the primary grasping region, and the
fingertip, thereby allowing the deformation behavior to be evaluated over the entire effective working length of the
finger under practical grasping conditions.
The compliant fingers were fabricated from TPU 95A because of its excellent flexibility, elastic recovery, and
fatigue resistance, making it suitable for repeated bending during grasping. In contrast, PLA was selected for the
supporting body owing to its higher stiffness, dimensional stability, and ease of fabrication by fused deposition
modelling. The rib geometry, including the inclination angle, spacing, thickness, and curvature radius, was
determined according to established Fin Ray design principles and refined through iterative CAD modelling and
finite element simulations to achieve an appropriate balance between structural stiffness, deformation capability,
and manufacturing feasibility.
Figure 2. Definition of three representative force application regions along the Fin Ray finger.
Figure 3. Representative displacement result for the selected middle contact region.
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Figure 4. Examples of rib configurations evaluated during the finger design process.
Table 2. Summary of the simulated Fin Ray finger variants.
Finger
type
Representative design
parameters
Main observation
Type 0
Baseline triangular
structure
Simple and easy to print; displacement about
10.73 mm in the main middle-contact case
Type 1
Rib angle about 12.54°;
rib thickness 1.6 mm;
spacing about 6 mm
Lower displacement but improved directional
deformation; installation orientation becomes
important
Type 2
Rib angle about 15°; rib
thickness 1.6 mm; spacing
about 5.44 mm
More uniform force distribution through
diagonal ribs and good structural stability
Type 3
Rib radius about 30 mm;
rib thickness about 1.06
mm; spacing about 8.57
mm
Largest displacement in the main case,
approximately 14.45 mm, and rapid surface
conforming behavior
The SolidWorks simulations were interpreted using the standard finite element equilibrium relation. For each
contact case, the base of the finger was fixed and a distributed load was applied on the selected contact region.
󰇛󰇜 with
󰇛 󰇜  (5)
where K(u) is the displacement dependent structural stiffness matrix, u is the nodal displacement vector, f is the
equivalent nodal force vector, is the strain tensor, is the stress tensor, and D is the elastic constitutive matrix.
The selected design should satisfy both deformation and strength requirements:
  
 (6)
where δmin is the minimum displacement required for surface wrapping, δallow is the allowable displacement, σvM is
the simulated von Mises stress, σy is the material yield or allowable stress, and SF is the design safety factor. The
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lower deformation limit ensures sufficient wrapping around the object, while the upper limit and the stress constraint
prevent structural failure of the printed TPU finger.
Table 3. Maximum and minimum displacement values extracted from the thesis simulation results.
Case
Type 0 max/min
(mm)
Type 1 max/min (mm)
Type 2 max/min
(mm)
Type 3 max/min
(mm)
TH1
6.263 / 1.253
1.90 / 0.38 to 2.07 / 0.207
2.89 / 0.578
5.1366 / 1.027
TH2
10.73 / 2.145
6.746 / 1.349 to 7.225 / 1.445
8.235 / 1.647
14.45 / 2.891
TH3
11.14 / 2.228
8.303 / 1.661 to 8.755 / 1.751
9.225 / 1.845
14.31 / 2.862
3. Prototype Fabrication and Control System
The final gripper is a three-finger mechanism. The flexible fingers are printed from TPU 95A, while the central
body, the finger mounts, and the transmission components are printed from PLA. FDM was selected because it
enables rapid iteration of rib geometry and low-cost manufacturing of both rigid and compliant components.
The closing and opening motion is generated by a stepper motor. Motor rotation is transmitted through a central
screw/slider mechanism that converts rotation into linear motion. This linear motion moves the linkage system
connected to the three fingers, causing the fingers to close for grasping or open for release. The gripper is controlled
by an Arduino Uno that sends step and direction signals to an A4988 driver. The driver supplies the stepper motor,
while the microcontroller defines the number of pulses and rotation direction.
The required motor torque can be estimated from the axial force demanded by the screw slider mechanism:
 (7)
where Tm is the required motor torque, Fc is the commanded clamping force, ps is the screw lead, and ηs is the
mechanical efficiency of the screw slider transmission. This equation provides the first order sizing criterion for
selecting the stepper motor and checking whether the actuation system can generate the required grasping force.
Figure 5. CAD model of the three finger Fin Ray gripper
assembly.
Figure 6. Fabricated prototype of the Fin Ray soft gripper.
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Figure 7. Control flow used for the Arduino based stepper motor actuation.
4. Experimental Evaluation
The prototype was evaluated using three objects selected to represent different grasping conditions. The apple
represents a quasi-spherical object with moderate surface stiffness, the plastic bottle represents a cylindrical object,
and the egg represents a fragile object requiring low gripping force. For each object, the gripping force was increased
gradually, and the grasping condition, curvature radius, and fingertip deflection were recorded. The simulation and
experimental curvature results were compared to evaluate the reliability of the design model.
The experimental procedure was conducted by placing the object at the center of the three fingers and increasing
the closing command until a stable grasp was achieved. The safe force range was defined as the range in which the
object could be held without visible damage or slip.
Each experiment was repeated three times under identical conditions, and the reported values represent the average
measurements. Finger deformation was recorded using a fixed-position camera and evaluated through image-based
displacement measurements to improve the repeatability of the comparison with the numerical simulations.
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Table 4. Experimental objects used to evaluate the gripper.
Object
Geometric
representation
Main
dimensions
Mass
Purpose of test
Apple
Sphere-like
Diameter 60 mm
240 g
Moderate load spherical grasping
Plastic
bottle
Cylinder
Height 200 mm;
diameter 60 mm
250 g
Cylindrical grasping with larger height
Egg
Fragile curved
body
Diameter about
35 mm
60 g
Low force grasping of damage
sensitive object
Figure 8. Experimental grasping tests using the fabricated gripper.
The finger curvature radius was treated as the principal validation quantity because it directly reflects the ability of
the compliant finger to conform to the object surface. When the deformed finger profile is approximated by a
circular arc, the curvature radius can be obtained from the chord length c and sagitta s:

 (8)
where R is the curvature radius of the deformed finger, c is the chord length of the approximated arc, and s is the
sagitta or maximum arc height. The discrepancy between experimental and simulated curvature radius was
quantified by the relative error:

  (9)
where ER is the relative curvature radius error, Rexp is the experimentally measured curvature radius, and Rsim is the
simulated curvature radius. The same procedure was applied to the apple, plastic bottle, and egg tests, allowing the
model data agreement to be evaluated under different object stiffness and geometry conditions.
For the apple, the gripper was stable over the tested range from 1.5 N to 5.0 N. The measured curvature radius
decreased from 213.71 mm at 1.5 N to 54.63 mm at 5.0 N, indicating that a higher clamping force produces stronger
wrapping deformation. The simulation experiment error ranged from 1.43% to 9.2%.
For the plastic bottle, the safe gripping range was larger, from 2.0 N to 7.0 N. The curvature radius decreased from
279.40 mm at 2.0 N to 62.65 mm at 7.0 N. The maximum deviation between simulation and experiment was 9.37%,
while the minimum error was 0.56%.
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For the egg, the allowable force range was limited to 1.0-3.5 N because of the fragile shell. The measured curvature
radius decreased from 327.11 mm to 187.61 mm over this range. The maximum error between simulation and
experiment was 11.22%, occurring at 2.5 N.
Figure 9. Curvature radius comparison between simulation and experiment for the three test objects.
Table 5. Summary of experimental curvature radius validation.
Object
Safe force range
Curvature radius trend
Simulation experiment error
Apple
1.5-5.0 N
213.71 mm to 54.63 mm
1.43%-9.2%
Plastic bottle
2.0-7.0 N
279.40 mm to 62.65 mm
0.56%-9.37%
Egg
1.0-3.5 N
327.11 mm to 187.61 mm
0.54%-11.22%
For a quasi-static grasp, the minimum condition for holding an object of mass m can be approximated by balancing
the available frictional force and the object weight:
   (10)
where μ is the friction coefficient at the finger object interface, Fn,i is the normal force generated by the i th finger,
m is the object mass, and g is gravitational acceleration. The safe operating force interval for each object is then
defined by
   (11)
where ΔFsafe is the safe operating force interval, Fmin is the minimum force that prevents slip, and Fmax is the
maximum force before excessive deformation, instability, or possible object damage. A larger ΔFsafe indicates a
wider operating margin for practical grasping.
The test results confirm the intended behavior of the Fin Ray structure. Increasing the clamping force reduces the
curvature radius and increases fingertip deflection, which means that the finger conforms more strongly to the object
surface. However, excessive force is undesirable for fragile objects. Therefore, the recommended operating force
must be selected according to object stiffness and allowable contact pressure.
The bottle permits the highest tested clamping force because its surface is less fragile and its cylindrical geometry
requires stronger lateral retention. The egg requires the lowest force range. The apple represents an intermediate
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condition. These results demonstrate that the same three finger architecture can be applied to objects of different
geometries if the actuation command is adjusted appropriately.
Figure 10. Summary of safe force range, curvature radius, and tip deflection for the three objects.
5. Discussion
The force curvature trend can be represented locally by a linear sensitivity coefficient:

 (12)
where SR is the local force curvature sensitivity and ΔR/ΔFc is the change in curvature radius per unit change in
clamping force. A larger SR indicates that the finger curvature changes rapidly with force, which is useful for
conformal grasping but may reduce controllability near fragile objects. This explains why the egg required a
narrower safe force range than the apple or plastic bottle.
The main design advantage of the proposed gripper is its passive compliance. The mechanical compliance of the
ribbed TPU fingers reduces the need for high precision control, because the finger geometry itself contributes to
shape adaptation. This characteristic is consistent with the general role of soft robotic grippers in unstructured
environments.
The simulation results indicate that rib geometry strongly affects the relationship between displacement and
structural stiffness. A highly compliant design provides better surface conformation but may reduce holding force
and durability. Conversely, a stiffer rib layout can generate larger grasping force but may reduce the ability to wrap
around fragile objects. Therefore, the finger should be selected based on task requirements rather than by
maximizing only one metric.
The numerical model adopted several simplifying assumptions to provide an efficient design-oriented evaluation.
The printed TPU was modelled as a linear elastic material, while its actual response is inherently hyperelastic under
large deformation. In addition, the simulation did not explicitly account for the anisotropic mechanical behaviour
introduced by the FDM printing process, variations in friction at the finger-object interface, or nonlinear contact
effects during grasping. Furthermore, the prototype employed open-loop stepper-motor actuation without force
feedback, limiting the direct validation of contact forces. Although these simplifications may contribute to the
discrepancies between simulation and experiment, the overall agreement demonstrates that the proposed model is
sufficiently accurate for preliminary design and comparative evaluation. Future work will incorporate hyperelastic
constitutive models, anisotropic material properties, nonlinear contact analysis, and closed-loop force sensing to
further improve predictive accuracy.
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The experimental errors between simulation and measurement are acceptable for a low-cost prototype, but several
factors can explain the remaining difference: simplified material properties in SolidWorks, anisotropy caused by
FDM printing, friction variation at the object finger interface, manual measurement error of curvature radius, and
open loop stepper motor actuation. Future work should include hyperelastic material characterization of printed
TPU, repeatability testing over many cycles, closed loop force or tactile feedback, and optimization of rib geometry
using a multi objective framework.
6. Conclusion
A three finger Fin Ray soft gripper was designed, fabricated, and experimentally evaluated. The soft fingers were
printed from TPU 95A and mounted on a PLA body actuated by a stepper motor. SolidWorks simulations showed
that the most effective contact region is located between one half and two thirds of the finger length from the base.
Among the tested rib configurations, the curved rib finger provided the largest displacement in the main contact
case, reaching approximately 14.45 mm.
The fabricated prototype successfully grasped an apple, a plastic bottle, and an egg. Stable grasping was achieved
within force ranges of 1.5-5.0 N, 2.0-7.0 N, and 1.0-3.5 N, respectively. The curvature radius validation showed
reasonable agreement between simulation and experiment, with maximum reported error of 11.22%.
In addition to validating the proposed prototype, this work establishes a reproducible CAD–FEA–fabrication–
experiment framework for Fin Ray gripper development. The comparison of different rib configurations, together
with the proposed analytical design equations and experimental validation, provides practical guidelines for future
soft-gripper design while offering an accessible low-cost platform for research and laboratory teaching.
The results demonstrate the feasibility of a low-cost Fin Ray gripper for adaptive handling of objects with different
shapes and fragility levels.
7. Authorship acknowledgments
Hoang Bui Huy: Conceptualization; Methodology; Investigation; Resources ; Data Analysis; Validation; Writing
– Review and Editing.
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Revista de Ciencias Tecnológicas (RECIT). Volumen 9 (3): e502.
14 ISSN: 2594-1925
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