VecTile: A Low-Cost Flexible Tactile Array for 3-DoF Force Sensing

Jian Hou; Xin Zhou; Adam J. Spiers

cs.ROOct 22, 2026

VecTile: A Low-Cost Flexible Tactile Array for 3-DoF Force Sensing

Authors: Jian Hou, Xin Zhou, Adam J. Spiers

Organizations: All authors are with the Manipulation and Touch Lab, Dept. Electrical and Electronic Engineering, Imperial College London.

Abstract

Tactile sensing provides robots with contact information difficult to obtain from vision alone. Shear force is particularly important for understanding tangential contact, guiding corrective motions, and maintaining grasp stability, yet flexible and low-cost tactile arrays often measure only normal force. We introduce VecTile, a low-cost, 6 mm thin, flexible tactile array capable of three-axis force sensing. VecTile combines a piezoresistive layer with passive silicone nubs that convert normal and shear forces into distinguishable pressure patterns. The sensor can be fabricated in-house without specialized equipment. The complete system costs less than 35 USD for a 4x4 array. We validate the sensing mechanism through finite element analysis and hardware experiments. In controlled single-taxel tests over 1-5 N normal force and up to 1.5 N shear force, VecTile achieves root-mean-square errors of 0.39 N and 0.16 N for normal and shear forces. A VecTile calibrated while flat retains accuracy when curved, while a five-minute manual calibration is sufficient for practical use. Two applications demonstrate its utility. First, shear readings are sensitive enough to stop a sharp scalpel from puncturing a balloon after contact. Second, the sensor substantially improves Diffusion Policy-guided power-plug insertion. All designs and code will be released upon paper acceptance. Project website: https://jiannnh.github.io/VecTile/.

Figures & tables

Fig. 1: VecTile on Fin-Ray type fingers during plug insertion. Color denotes normal response and arrows indicate shear magnitude and direction.

Fig. 2: VecTile design. (A) The FPC implements a $4\times 4$ taxel array, with four quadrants beneath each nub-based taxel, addressed as an $8\times 8$ row–column matrix. During scanning, one column is driven at a time, while one row is connected to the virtual-ground front end. Compression reduces the resistance of the silver-fiber resistive layer, increasing current between paired electrodes within a quadrant. (B) The assembled sensor stacks the cast silicone and resistive layer over the FPC. Normal force raises the four quadrant readings uniformly, whereas shear creates across-quadrant difference.

Fig. 3: Finite element analysis of the nub-lever mechanism. (A) Force encoding and mechanical separability for a $3.0~\mathrm{mm}$ nub. (i) Under a $2~\mathrm{N}$ normal preload, the $+x$ and $-x$ half-plane forces are equal. Applying $1~\mathrm{N}$ of shear shifts the contact pressure toward the leading half, producing a differential $D$ . (ii) Simulated loads mapped into the $(\Sigma,D)$ reading space. Normal-force increments (blue) move mainly along $\Sigma$ , whereas shear-force increments (red) move mainly along $D$ . Each $(\Sigma,D)$ reading maps to a unique $(F_{z},F_{x})$ pair over the simulated positive- $x$ range. (B) Effect of nub height on the mechanical response. (i) Normal force against indentation depth. (ii) Total contact force $\Sigma$ within the nub footprint against applied normal force $F_{z}$ . (iii) Differential $D$ against applied shear shows the increase in shear gain with nub height; the lines show the $2~\mathrm{N}$ preload, and the shaded bands show $D$ ’s span across the $1$ – $5~\mathrm{N}$ preload range.

Fig. 4: VecTile fabrication. (1) Mold release is applied to the 3D-printed PLA mold components. (2) Dragon Skin 30 is mixed and vacuum-degassed. (3) The bottom plate is filled with the degassed silicone, after which the dummy FPC and spacer are positioned and a second pour completes the mold stack. (4) The mold is closed, clamped, and cured for $16~\mathrm{h}$ ; the silicone layer is then de-molded and the dummy FPC is slid out. (5) Cyanoacrylate glue dots are applied only at the marked locations on the FPC. (6) The resistive layer is placed over the FPC. (7) The FPC and resistive layer are slid into the molded silicone layer produced in step (4). (8) A small batch of Dragon Skin 30, prepared as in step (2), is injected through the openings; the bottom plate from step (1) is reused as a press under a $200~\mathrm{g}$ load during the approximately $8~\mathrm{h}$ cure.

	Item	Cost (USD)
Sensor	FPC (30-pc order)	0.89
	Resistive layer ( $\approx$ 0.004 m 2 at $30/m 2 )	0.12
	Dragon Skin 30 ( $\approx$ 15 g at $20/lb trial kit)	0.70
	FFC cable + connector set	1.50
	Mold filament ( $\approx$ 30 g at $12/kg)	0.36
	Subtotal	3.57

TABLE I: Bill of Materials

Fig. 5: Left: VecTile without the silicone layer mounted on an ATI Mini40 force/torque sensor, with a guide plate aligning the loading pin to each taxel. Right: Per-quadrant ADC response to normal force; the shaded envelope spans 64 quadrants. The quadratic is fitted over $F_{z}\leq 1.25~\mathrm{N}$ .

Fig. 6: Sensor characterization. (A) Experimental setup for flat and $R=85~\mathrm{mm}$ curved mountings. (B) Data collection procedure.

Fig. 7: Measured response and manual force decoding. (A) Effect of nub height on (i) stiffness, (ii) the normal-force feature $\Sigma$ , and (iii) the shear-force feature $D$ . Solid lines are the median while the bands show the range, both across 16 taxels. (B) Manual bench validation of a $3.0~\mathrm{mm}$ VecTile mounted on an ATI Mini40: hand loading (left) and a real-time comparison between the VecTile estimates and F/T reference measurements (right).

RMSE (N)	Nub height (mm)				Curved, 3.0 mm
	0.6	1.0	2.0	3.0	convex	concave
$F_{z}$	0.45 $\pm$ 0.06	0.45 $\pm$ 0.05	0.41 $\pm$ 0.04	0.39 $\pm$ 0.03	0.45 $\pm$ 0.06	0.42 $\pm$ 0.04
Shear	0.29 $\pm$ 0.04	0.28 $\pm$ 0.04	0.24 $\pm$ 0.03	0.16 $\pm$ 0.02	0.21 $\pm$ 0.04	0.23 $\pm$ 0.03

TABLE II: Force RMSE across nub heights and curved mounts.

Fig. 8: VecTile demonstrations. (A) Scalpel–balloon reflex: (i) shear measured during a burst trial and (ii) shear-triggered retraction before puncture. (B) Visuotactile plug insertion: (i) Hardware setup and (ii) Camera views and fingertip tactile readings during a 3-DoF tactile sensing plug-insertion rollout.

Observation	Successful trials	Direct inserts	Successful corrections
Vision only	12/25 (48%)	5	7/20 (35%)
+ normal tactile	16/25 (64%)	2	14/23 (61%)
+ 3-DoF tactile	22/25 (88%)	4	18/21 (86%)

TABLE III: Plug-insertion performance at unseen locations.

Tactile Sensing

Tactile sensing measures contact forces, deformation, texture, and motion to help robots perceive and act through physical interaction.

See all 138 papers

FlexiTac: A Low-Cost, Open-Source, Scalable Tactile Sensing Solution for Robotic Systems
Apr 30, 2026Binghao Huang, Yunzhu LiTactile Sensing Tactile Sensing for Robotic Manipulation
Columbia University
Scalable Open-Source Visuotactile Sensor for 6-Axis Contact Wrench Estimation in Tensegrity Robots
Jul 17, 2026Wenzhe Tong, Jonathan Mi, Xili Yi +2Vision-Based Tactile Sensing Tensegrity Robotics
Robotics Department, University of Michigan, Ann Arbor, MI, 48109, USA
Hall Effect-Based Tactile Force Detection Sensor for Robot-Assisted Minimally Invasive Surgery
Oct 7, 2026Charles DeLorey, Michael Brockdorff, Adam Metcalf +3Tactile Sensing Robotic Tactile Sensing
STORM Lab, School of Electronic and Electrical Engineering, University of Leeds, Leeds, UK

Apr 30, 2026J/K move · Enter open · S save

FlexiTac: A Low-Cost, Open-Source, Scalable Tactile Sensing Solution for Robotic Systems

Binghao Huang, Yunzhu Li

Columbia University

Tactile Sensing Tactile Sensing for Robotic Manipulation Robotic Tactile Sensing

Open paper AskPDF arXiv

We present FlexiTac, a low-cost, open-source, and scalable piezoresistive tactile sensing solution designed for robotic end-effectors. FlexiTac is a practical "plug-in" module consisting of (i) thin, flexible tactile sensor pads that provide dense tactile signals and (ii) a compact multi-channel readout board that streams synchronized measurements for real-time control and large-scale data collection. FlexiTac pads adopt a sealed three-layer laminate stack (FPC-Velostat-FPC) with electrode patterns directly integrated into flexible printed circuits, substantially improving fabrication throughput and repeatability while maintaining mechanical compliance for deployment on both rigid and soft grippers. The readout electronics use widely available, low-cost components and stream tactile signals to a host computer at 100 Hz via serial communication. Across multiple configurations, including fingertip pads and larger tactile mats, FlexiTac can be mounted on diverse platforms without major mechanical redesign. We further show that FlexiTac supports modern tactile learning pipelines, including 3D visuo-tactile fusion for contact-aware decision making, cross-embodiment skill transfer, and real-to-sim-to-real fine-tuning with GPU-parallel tactile simulation. Our project page is available at https://flexitac.github.io/.

Abstract

Tactile Sensing

Explore similar work

FlexiTac: A Low-Cost, Open-Source, Scalable Tactile Sensing Solution for Robotic Systems

Scalable Open-Source Visuotactile Sensor for 6-Axis Contact Wrench Estimation in Tensegrity Robots

Hall Effect-Based Tactile Force Detection Sensor for Robot-Assisted Minimally Invasive Surgery