Ori-Sense: origami capacitive sensing for soft robotic applications

Hugo de Souza Oliveira; Xin Li; Mohsen Jafarpour; Edoardo Milana

cs.ROFeb 20, 2026

Ori-Sense: origami capacitive sensing for soft robotic applications

Authors: Hugo de Souza Oliveira, Xin Li, Mohsen Jafarpour, Edoardo Milana

Abstract

This work introduces Ori-Sense, a compliant capacitive sensor inspired by the inverted Kresling origami pattern. The device translates torsional deformation into measurable capacitance changes, enabling proprioceptive feedback for soft robotic systems. Using dissolvable-core molding, we fabricated a monolithic silicone structure with embedded conductive TPU electrodes, forming an integrated soft capacitor. Mechanical characterization revealed low stiffness and minimal impedance, with torque values below 0.01 N mm for axial displacements between -15 mm and 15 mm, and up to 0.03 N mm at 30 degrees twist under compression. Finite-element simulations confirmed localized stresses along fold lines and validated the measured torque-rotation response. Electrical tests showed consistent capacitance modulation up to 30%, directly correlated with the twist angle, and maximal sensitivity of S_theta ~ 0.0067 pF/deg at 5 mm of axial deformation.

Figures & tables

Fig. 1: Concept of the Ori-Sense soft origami capacitor. The inverted Kresling structure translates torsional deformation into a measurable capacitance change, enabling proprioceptive sensing in soft robotic systems.

Fig. 2: Design of the origami structure: (a) Initial hexagon and point rotation by $\beta$ . (b) Formation of faces $F_{1}$ and $F_{2}$ . (c) Mirroring through a symmetry plane. (d) Circular array construction. (e) Linear array extension. (f) Addition of top and bottom lids. (g) Final assembled structure.

Fig. 3: Fabrication of the soft origami capacitive sensor: (a) Printing of BVOH core, addition of the capacitive plates and molding prepararton. (b) Mold assembly and silicone injection. (c) Core dissolution after curing. (d) 3D-printed core. (e) Conductive TPU plates. (f) Core with plates before molding. (g) Capacitive plates arrangement in silicone. (h) Final soft structure with integrated electrodes.

Fig. 4: Mechanical response of the inverted Kresling origami sensor: (a) Von Mises stress distribution at $30\text{\,}\mathrm{\SIUnitSymbolDegree}$ of rotation. (b) Comparison between experimental and FEM torque–rotation curves at zero axial strain, together with extreme cases. (c) Torque–rotation curves for varying axial displacements. (d) Peak torques for the structure. (e) Axial force versus rotation angle for different axial offsets. (f) Peak axial force and torque, indicating symmetric trends between tensile and compressive deformation.

Fig. 5: Electrical characterization of the soft origami capacitive sensor. (a) Normalized sensor output during repeated torsional cycles (

0\text{\,}\mathrm{\SIUnitSymbolDegree}

–

30\text{\,}\mathrm{\SIUnitSymbolDegree}

) for axial displacements of

-15\text{\,}\mathrm{mm}-10\text{\,}\mathrm{mm}-5\text{\,}\mathrm{mm}0\text{\,}\mathrm{mm}5\text{\,}\mathrm{mm}10\text{\,}\mathrm{mm}15\text{\,}\mathrm{mm}

. (b) Normalized signal for the case of

-15\text{\,}\mathrm{mm}

axial displacement. (c) Normalized signal for

-10\text{\,}\mathrm{mm}

. (d) Normalized signal for

-5\text{\,}\mathrm{mm}

. (e) Normalized signal for

0\text{\,}\mathrm{mm}

. (f) Normalized signal for

10\text{\,}\mathrm{mm}

. (g) Normalized signal for

15\text{\,}\mathrm{mm}

Explore similar work

External Photoreflective Tactile Sensing Based on Surface Deformation Measurement
Nov 9, 2025Seiichi Yamamoto, Hiroki Ishizuka, Takumi Kawasetsu +6Tactile Sensing Tactile Sensing for Robotic Manipulation
Graduate School of Engineering Science, The University of Osaka, Toyonaka 560-0043, Japan
Effect of Twisted-Yarn Architecture on Pressure and Proximity Sensing Characteristics of Textile Capacitive Sensors for Robotic Skin
Aug 14, 2026Ishtia Zahir, Eslam Saleh, Maryam Rezayati +2Tactile Sensing Robotic Tactile Sensing
V-Trion GmbH, Millennium Park 15, 6890 Lustenau, Austria · Institute of Mechatronic Systems, ZHAW Zurich University of Applied Sciences, Winterthur, Switzerland · Grabher Group GmbH, Augarten Strasse 27, 6890 Lustenau, Austria
Surface-based Manipulation Using Tunable Compliant Porous-Elastic Soft Sensing
Feb 24, 2026Gayatri Indukumar, Muhammad Awais, Diana Cafiso +2Robotic Manipulation Soft Robotics
Soft BioRobotics Perception Group at Istituto Italiano di Tecnologia, 16163, Genova, Italy · University of Genoa, 16126, Genova, Italy · Biorobotics Institute, Scuola Superiore Sant’Anna, Pontedera, 56025, Italy +1

Nov 9, 2025J/K move · Enter open · S save

External Photoreflective Tactile Sensing Based on Surface Deformation Measurement

Seiichi Yamamoto, Hiroki Ishizuka, Takumi Kawasetsu, Koh Hosoda+5

Graduate School of Engineering Science, The University of Osaka, Toyonaka 560-0043, Japan

Tactile Sensing Tactile Sensing for Robotic Manipulation Robotic Tactile Sensing Soft Robotics

Open paper AskPDF arXiv

We present a tactile sensing method enabled by the mechanical compliance of soft robots; an externally attachable photoreflective module reads surface deformation of silicone skin to estimate contact force without embedding tactile transducers. Locating the sensor off the contact interface reduces damage risk, preserves softness, and simplifies fabrication and maintenance. We first characterize the optical sensing element and the compliant skin, thendetermine the design of a prototype tactile sensor. Compression experiments validate the approach, exhibiting a monotonic force output relationship consistent with theory, low hysteresis, high repeatability over repeated cycles, and small response indentation speeds. We further demonstrate integration on a soft robotic gripper, where the module reliably detects grasp events. Compared with liquid filled or wireembedded tactile skins, the proposed modular add on architecture enhances durability, reduces wiring complexity, and supports straightforward deployment across diverse robot geometries. Because the sensing principle reads skin strain patterns, it also suggests extensions to other somatosensory cues such as joint angle or actuator state estimation from surface deformation. Overall, leveraging surface compliance with an external optical module provides a practical and robust route to equip soft robots with force perception while preserving structural flexibility and manufacturability, paving the way for robotic applications and safe human robot collaboration.

Abstract

Explore similar work

External Photoreflective Tactile Sensing Based on Surface Deformation Measurement

Effect of Twisted-Yarn Architecture on Pressure and Proximity Sensing Characteristics of Textile Capacitive Sensors for Robotic Skin

Surface-based Manipulation Using Tunable Compliant Porous-Elastic Soft Sensing