Original research asset

RoboSkin Tactile Research Index

The RoboSkin Tactile Research Index compares public robot-skin and tactile-AI work by sensing principle, measured modalities, form factor, data output, application direction, evidence level, and explicit limitations. Every record links to its public source and a RoboSkin.ai research brief so readers can verify context before using the taxonomy.

Open CSV data Open JSON data Open GitHub repository ↗Browse research briefs

RoboSkin tactile research index cover showing a robot hand, sensor layers, and structured data signals.

30: reviewed records
4: evidence classes
2026-08-22: edition reviewed

Versioned public release

A stable research asset, not a changing article list

Version: v2026.08.22
Data license: CC BY 4.0
Records: 30

Open versioned release ↗Read the data license ↗

Citation

Cite the index with its reviewed version

Cite the version you actually reviewed. The GitHub release preserves matching CSV and JSON files while this page remains the canonical human-readable route.

RoboSkin.ai Editorial Team. (2026). RoboSkin Tactile Research Index (v2026.08.22) [Data set]. RoboSkin.ai. https://roboskin.ai/research-index

BibTeX-compatible entry

@misc{roboskin_tactile_research_index_2026,
  author  = {{RoboSkin.ai Editorial Team}},
  title   = {RoboSkin Tactile Research Index},
  year    = {2026},
  version = {v2026.08.22},
  url     = {https://roboskin.ai/research-index},
  note    = {Source-reviewed public release; CC BY 4.0}
}

ModalityEvidenceYear

Showing 30 of 30 records

Research item	Year	Sensor principle	Modalities	Form factor	Data output	Applications	Evidence
UniVTAC separates tactile simulation, representation learning, and policy evaluation arXiv: UniVTAC: A Unified Simulation Platform for Visuo-Tactile Manipulation Data Generation, Learning, and Benchmarking UniVTAC is a February 10, 2026 arXiv v1 preprint. Its 205,826 encoder samples, 400 paper policy-training trajectories, public 800-episode benchmark release, 450 physical demonstrations, and evaluation rollouts are different units. Paper Table I reports 30.9% for vision-only ACT and 48.0% with the UniVTAC Encoder, a 17.1-percentage-point change; hosted checkpoint logs instead average 32.375 and 43.5 and should not be described as reproducing that table. The public workflow currently supports simulated GelSight Mini collection and evaluation, while GF225 and Xense paths remain marked planned or TODO. Repository, dataset, and checkpoint licensing also require separate treatment. Reviewed 2026-08-22	2026	Simulation-generated marker-based visuo-tactile observations encoded by a 512-dimensional ResNet-18 representation model with shape, contact-deformation, marker-position, and relative-pose supervision	simulated marked tactile RGB, simulated marker-free tactile RGB, simulation depth, projected marker coordinates, relative object pose, robot vision and state, physical ViTai GF225 tactile RGB at 30 Hz	Simulated bilateral GelSight Mini on a Franka Panda benchmark configuration plus a separate physical Tianji Marvin arm with bilateral ViTai GF225 sensors	205,826 encoder-pretraining samples; an eight-task benchmark; a pinned public 800-episode HDF5 release; 512-dimensional tactile features; and protocol-bounded simulated and physical policy success rates	visuo-tactile simulation, tactile representation learning, contact-rich robot manipulation, tactile benchmark evaluation, sim-to-real manipulation	preprint
Vision-based tactile intelligence connects sensor optics to robot action arXiv: Vision-Based Tactile Intelligence for Robotics: Sensing, Learning, and Embodied Manipulation This August 16, 2026 arXiv v1 source is a review rather than an original controlled benchmark, sensor release, dataset, or model artifact. Its taxonomy synthesizes prior literature and is not an industry standard; individual performance, availability, license, and scale claims still require the cited primary sources. No dedicated official project, code, or dataset link was displayed on the reviewed arXiv record on 2026-08-22. Reviewed 2026-08-22	2026	Review taxonomy of camera-based tactile sensing that converts compliant-interface deformation into optical images for geometric, force-related, temporal, and learned inference	tactile image, direct contact geometry, model-mediated force-related cues, temporal contact and slip information, vision-touch-language-action alignment	Survey spanning fingertip, manipulator-integrated, miniature, all-around, and large-area vision-based tactile sensor designs	Source-organized map from contact deformation and optical readout through tactile representations, multimodal learning, simulation, datasets, and manipulation policies	vision-based tactile sensing, contact-rich manipulation, tactile representation learning, tactile foundation models, robot skin research mapping	preprint
ADEPT reports a 3/10 to 8/10 tactile ablation on dexterous insertion arXiv: ADEPT reinforcement-learning preprint The matched tactile comparison is restricted to one Flexiv-Sharpa square-and-round insertion condition with ten physical trials per modality: 3/10 final success for vision-only and 8/10 for visuo-tactile. Each task and embodiment is trained independently; KUKA experiments are vision-only; both systems are fixed workbenches; and no public training code, weights, checkpoint, dataset, or artifact license was verified on 2026-08-22. Reviewed 2026-08-22	2026	Per-finger TacMap encoding of vision-based fingertip penetration depth, thresholded contact, and fingertip position for the Flexiv-Sharpa student only	two RGB camera views, robot proprioception, five fingertip TacMap representations on Flexiv-Sharpa, five fingertip positions on Flexiv-Sharpa, joint-space robot action	Separate fixed-workbench KUKA iiwa7 plus Allegro Hand and Flexiv Rizon plus Sharpa-hand research configurations	Embodiment-specific reinforcement-learning policies mediated by a full joint-configuration-space geometric fabric	dexterous insertion, long-horizon manipulation, visuo-tactile robot learning, zero-shot sim-to-real policy transfer	preprint
PRISM maps 5,000+ contact-rich industrial robot trajectories arXiv: PRISM: Precision and contact-rich Real-world Industrial Skill dataset with Multimodal sensing The tactile stream covers only an unspecified subset of episodes, and the approximately 27M images combine visual and visuotactile streams. Although the abstract says the dataset is open-sourced, the official project still labels the dataset “soon” and the GitHub repository exposes no dataset files, release, or dataset-file license as of 2026-08-22. Author-reported policy experiments remain tied to selected Realman tasks and are not an independent benchmark. Reviewed 2026-08-22	2026	Synchronized multi-view RGB-D, high-rate force/torque, robot state, and subset-only visuotactile sensing across industrial teleoperation platforms	multi-view RGB, depth, visuotactile image when available, 6DoF force/torque when available, robot joint angle and torque, end-effector pose, gripper state, human control signal, calibration and timestamps	Contact-rich industrial data collection across dual Franka Emika Panda, bimanual Realman RM75-6F, and LEJU upper-body humanoid platforms	5,000+ robot trajectories paired with 5,000 human demonstrations, 45+ hours, and approximately 27M images across visual and visuotactile streams	industrial robot learning, contact-rich manipulation, multimodal policy evaluation, teleoperation data analysis	preprint
The Missing Touch tests spatial tactile feedback in robot teleoperation arXiv: The Missing Touch: Spatially Distributed Tactile Feedback Brings Teleoperation Closer to Human Dexterity The abstract’s 29–79% reduction refers to deviation between teleoperated and natural trajectories under study-specific DTW comparisons, not autonomous-policy success or a universal dexterity gain. Evidence comes from a 2-DoF device, two tasks, 12 button-task participants and a separate 10-person peg-rolling group; Full feedback was not superior in every corrected comparison, and no autonomous policy was trained or evaluated. Reviewed 2026-08-22	2026	GelSight Mini contact images mapped to a 32-DoF spatially programmable cutaneous fingertip display with bilateral kinesthetic force feedback	vision-based tactile image, binary spatial cutaneous feedback pattern, kinesthetic force feedback, 2D end-effector trajectory, participant questionnaire	Custom 2-DoF leader-follower telemanipulator evaluated with button discrimination and peg rolling	50 Hz trajectories, DTW similarity to direct manipulation, task-specific errors, completion time, variability, and perceived workload	robot teleoperation, haptic feedback, learning-from-demonstration data collection, contact-rich manipulation	preprint
Tac4Loco uses plantar pressure to adapt humanoid locomotion arXiv: Tac4Loco plantar pressure humanoid locomotion preprint Tac4Loco is an arXiv v1 preprint on one Unitree G1 and one bilateral 60-taxel-per-foot FSR layout. Training occurs in simulation; physical comparisons generally use ten trials per configuration; the gravel demonstration is qualitative; and “zero-shot” refers only to the paper’s unseen compliant and granular conditions. Code and experiment configurations are announced for future release, but no dedicated artifact repository or license was verified on 2026-08-22. Reviewed 2026-08-22	2026	Topology-preserving ordinal encoding of bilateral plantar pressure with state-conditioned spatial and temporal pressure-proprioception branches	60-element FSR pressure array per foot, proprioception, pressure history, simulated contact force, whole-body joint action	Unitree G1 trained in MJLab simulation and deployed physically with bilateral plantar-pressure insoles	Spatial and temporal plantar-support representations fused into a 50 Hz learned locomotion policy	humanoid locomotion, post-contact terrain adaptation, plantar tactile sensing, sim-to-real control	preprint
SoftVTBench separates deformable-task completion from contact quality arXiv: SoftVTBench deformation-aware visuo-tactile dataset and benchmark preprint The paper and Hugging Face dataset-card revision fd2793a describe 4,000 demonstrations, while the older GitHub README still lists 1,628 demonstrations and 33 assets; the first-party release documents are not synchronized. All data and evaluation are simulated, no SoftVTBench-specific sim-to-real validation is reported, and DSR is a paper-defined metric rather than an industry standard. Reviewed 2026-08-22	2026	Simulated dual-finger GelSight Mini RGB and marker-motion rendering with evaluator-only FEM deformation state	simulated multi-view RGB, simulated tactile RGB, simulated tactile marker motion, proprioception, language, robot actions, evaluator-only FEM state	Isaac Sim and Isaac Lab deformable-object manipulation with a simulated Franka arm, Panda gripper, and bilateral GelSight Mini profiles	Expert demonstration trajectories plus Task Success Rate, Deformation-aware Success Rate, and normalized deformation traces	deformable-object manipulation, visuo-tactile policy learning, interaction-quality evaluation	preprint
HiTac-WAM forecasts contact, deformation, and slip before robot action arXiv: HiTac-WAM hierarchical tactile world action model preprint Author-reported evidence from three task-specific real-robot setups and matched training budgets; cross-hardware transfer, independent replication, and a public code or dataset release were not established on the reviewed source page. Reviewed 2026-08-21	2026	Hierarchical tactile forecasting from contact state to 3D deformation and slip risk	video context, robot action chunks, contact state, 3D tactile deformation, slip risk	Contact-rich robot manipulation evaluated on chip grasping, blackboard erasing, and USB insertion	Candidate-conditioned tactile forecasts, task-progress estimates, selected action chunks, and discrepancy-triggered replanning signals	contact-aware planning, tactile world-action modeling, online manipulation correction	preprint
T-Rex adds high-rate tactile reaction to dexterous robot policies arXiv: T-Rex tactile-reactive dexterous manipulation preprint The authors report 65% average success for T-Rex versus 35% for EgoScale, an absolute gap of 30 percentage points across 12 tasks with 16 rollouts per task. The result is tied to one Dexmate Vega-1 and Sharpa Wave setup, and the approximately 50-hour public subset is not the complete reported 100-hour training corpus; neither result is an independent cross-platform benchmark. Reviewed 2026-08-22	2026	Variable-rate visual-language-action modeling with a temporal tactile VQ-VAE	vision, language instruction, robot action, high-frequency tactile signal	Tactile-reactive dexterous manipulation across 12 author-reported tasks	Temporal tactile tokens and action predictions trained with a reported 100-hour collection; the official dataset card now exposes 5,464 episodes and 5,473,459 frames at 30 FPS, approximately 50 hours, in a LeRobot v3.0 subset	delicate force control, deformable-object manipulation, tactile-reactive VLA policies	preprint
RoboTacDex maps 6,000+ humanoid visual-tactile trajectories arXiv: RoboTacDex humanoid visual-tactile-action dataset preprint The June 2026 v1 preprint says the dataset will be open-sourced soon; no official package, repository, public file format, or dataset license was verified, and evaluation remains tied to one fixed-lower-body Unitree G1 configuration. The text reports 23 skills while Figure 4 exposes 22 discernible atomic-skill labels. Reviewed 2026-08-22	2026	Four-view RGB-D synchronized with bilateral fingertip force, self-capacitance proximity, robot states, actions, and semantic annotations	four-view RGB, four-view depth, normal and tangential fingertip force, self-capacitance proximity, robot state, robot action, semantic annotation	Unitree G1 with fixed lower body, dual arms totaling 14 DoF, and two BrainCo Revo2 Tactile hands totaling 12 hand DoF as counted by the paper	More than 6,000 trajectories totaling approximately 25 hours across 19 tasks, an author-reported 23 skills, and 22 objects	humanoid imitation learning, dual-arm dexterous manipulation, visual-tactile-action learning	preprint
TactiDex benchmarks contact-level human-to-robot dexterity arXiv: TactiDex tactile-guided dexterous manipulation benchmark preprint The reviewed abstract reports stronger success and physical realism without supplying a universal cross-hardware score; conclusions remain bound to the authors’ tasks, systems, metrics, and preprint evaluation. Reviewed 2026-08-21	2026	Alignment of whole-hand tactile signals with multi-granularity kinematic and object states	whole-hand tactile signal, kinematic state, object state, human demonstration	Real-world tactile-guided benchmark covering single-hand and bimanual dexterous tasks	Aligned demonstration data, standardized evaluation metrics, and a tri-component tactile reward	human-to-robot skill transfer, contact-level manipulation evaluation, tactile-guided dexterity	preprint
FeelWorld predicts contact, tactile force states, and slip for robot planning arXiv: FeelWorld visuo-tactile world model preprint Preprint evidence tied to three reported task setups, sensors, robot system, baselines, and planning protocol; LPIPS is not a direct force, slip, safety, or transfer metric. Reviewed 2026-08-15	2026	Action-conditioned hierarchical visual-tactile world modeling	visual latent, contact state, force-related 3D tactile latent, slip state, robot action	Contact-aware world model evaluated on chip grasping, fruit grasping, and USB insertion	Predicted visual futures, contact state, tactile latent, and slip state for contact-aware planning	contact prediction, zero-shot robot planning, contact-rich manipulation	preprint
HT-Bench full-hand tactile benchmark for robot manipulation arXiv: HT-Bench full-hand tactile representation benchmark preprint v2 The v2 preprint is tied to one reported egocentric/full-hand tactile sensing pipeline. The authors list fingertip optical tactile sensors, force/torque sensors, skin-like taxel arrays, and non-hand embodiments as uncovered. The 68.3% HandTouch mean versus the strongest baseline mean of 50.0% comes from four tasks with 15 trials each and no reported confidence intervals or significance test; it is not universal generalization evidence. Data, protocols, weights, and scripts are promised for future release and were not verified as downloadable on 2026-08-22. Reviewed 2026-08-22	2026	Egocentric vision and full-hand tactile representation learning	egocentric RGB vision, full-hand tactile frames	Single reported egocentric/full-hand tactile pipeline spanning 226 data-collection tasks, plus four downstream real-robot tasks with 15 trials per method and task	10M RGB frames and 7.8M tactile frames, four representation-learning tracks, and source-reported downstream task success rates	tactile representation learning, dexterous manipulation, cross-modal prediction, bounded downstream robot evaluation	preprint
Dream-Tac: A Unified Tactile World Action Model for Contact-Rich Robot Manipulation arXiv: Dream-Tac tactile world action model preprint Preprint evidence; transfer across sensors, tasks, and deployment conditions still requires independent validation. Reviewed 2026-07-10	2026	Tactile world-action modeling	tactile observation, robot action	Contact-rich robot manipulation system	Predicted tactile observations conditioned on robot actions	contact prediction, robot manipulation	preprint
Single-material soft robotic skin for multimodal e-skin sensing Science Robotics: Science Robotics peer-reviewed single-layer soft sensory skin article The 33 kHz maximum applies to one electrode configuration, while all 1,726,080 channels are reported at 0.02 Hz; durability, production integration, and real-world robotic-task testing remain open. Reviewed 2026-08-22	2025	Single-layer conductive hydrogel with high-density electrical impedance tomography	touch and insulated presses, strain and proprioception, damage, local heating, temperature and humidity	Full-size hollow hydrogel hand with 32 wrist electrodes	Up to 863,040 electrode configurations yielding 1,726,080 amplitude-and-phase information channels	robot body sensing, multimodal e-skin	peer-reviewed
FreeTacMan robot-free visuo-tactile data collection for tactile AI arXiv: FreeTacMan robot-free visuo-tactile data collection preprint Preprint evidence; dataset diversity and transfer to other tactile hardware remain evaluation questions. Reviewed 2026-07-10	2025	Robot-free visuo-tactile data collection	vision-based touch, contact motion	Portable tactile data-collection workflow	Paired tactile observations and interaction trajectories	tactile dataset collection, manipulation learning	preprint
Sparsh-X multisensory touch representations for tactile AI arXiv: Sparsh-X multisensory touch representations preprint Preprint evidence; downstream performance depends on sensor coverage, task data, and evaluation protocol. Reviewed 2026-07-10	2025	Multisensory tactile representation learning	tactile images, audio, motion, pressure	Digit 360 multisensory tactile representation model	Reusable latent touch representations	physical property inference, contact-rich manipulation	preprint
GenForce transferable force sensing for robot skin and tactile sensors Nature Communications: Nature Communications GenForce tactile sensing article Published evaluation does not establish equivalent accuracy for every sensor geometry, material, or deployment environment. Reviewed 2026-07-10	2026	Cross-sensor force estimation through shared marker representations	three-axis force, optical and electronic tactile signals	Framework spanning GelSight, TacTip, and uSkin sensors	Estimated contact-force vectors	force-aware manipulation, sensor transfer	peer-reviewed
MiTaS multi-resolution tactile imitation learning for robot hands arXiv: MiTaS multi-resolution tactile imitation learning preprint Preprint evidence; benefits may depend on task dynamics, sensor timing, and the selected imitation-learning policy. Reviewed 2026-07-10	2026	Multi-resolution tactile imitation learning	vision-based touch, event-based touch	Tactile robot-hand learning pipeline	Time-aligned multisensor tactile features and robot actions	imitation learning, dexterous manipulation	preprint
ROS 2 tactile sensor pipeline for robot skin data replay Open Robotics documentation and RoboSkin.ai analysis: ROS 2 and ros2_control Kilted documentation Architecture guidance rather than a benchmark; message design and timing requirements remain application-specific. Reviewed 2026-07-10	2026	ROS 2 tactile data transport and synchronization	pressure, shear, slip, temperature	Robot middleware pipeline	Timestamped tactile messages, transforms, and replayable logs	robot integration, tactile dataset logging	documentation
GIST humanoid visual-tactile-action dataset maps 101.9K soft-object samples GIST arXiv preprint: GIST humanoid visual-tactile-action dataset preprint, arXiv v2 One unnamed humanoid embodiment, two soft objects, four pressure conditions, and three operators; as of 2026-08-22 no official dataset download, code, project page, or dataset license was verified, and the arXiv CC BY license covers the article rather than unpublished data files. Reviewed 2026-08-22	2025	Dense humanoid-hand tactile sensing synchronized with vision, proprioception, and actions	848 × 480 egocentric vision, RealSense D435 third-person vision, dense hand tactile pressure, piezoresistive carpet pressure, arm and finger proprioception, robot actions	Unnamed teleoperated humanoid with two Inspire RH56-DFX hands and 1,062 tactile sensing units per hand	101.9K visual-tactile-action samples with 2,124 total hand tactile values	soft-object manipulation learning, visual-tactile-action policy training, dense tactile representation research	preprint
Wet slippage detection for bionic fingertip e-skin Scientific Reports: Scientific Reports wet slippage bionic fingertip e-skin article Classification used 120 mixed-condition signals and a small set of food objects; closed-loop grip correction, abrasion, cleaning, and long-term surface wear were not demonstrated. Reviewed 2026-07-21	2026	Fingerprint-patterned ferroelectric piezoelectric microvibration sensing	dynamic slip microvibration, surface-material and wetness-dependent waveform	Fully printed flexible fingertip e-skin mounted on a soft robotic hand	Slip-voltage waveforms with FFT and STFT features for wetness and surface classification	wet and oily slip detection, robotic grasp monitoring, surface-material classification	peer-reviewed
Energy constrained touch encoding for large-area e-skin Nature Communications: Nature Communications bioinspired spiking touch encoding article The work is a 135 cm2 contact-localization demonstrator; error increased with contact count and body-scale transfer was not shown. Reviewed 2026-07-21	2026	Fiber Bragg Grating strain sensing with event-driven spiking neural decoding	contact strain, spike-encoded touch events, single- and multi-touch location	135 cm2 silicone forearm-shaped e-skin with 21 FBGs on one optical fiber and a neuromorphic processor	FBG wavelength shifts converted to spike trains and decoded into two-dimensional contact positions	large-area touch localization, energy-constrained robotic skin, safe human-robot interaction	peer-reviewed
Origami capacitive robotic e-skin for large-area tactile sensing npj Flexible Electronics: npj Flexible Electronics origami capacitive robotic e-skin article Adjacent loads can merge, proximity sensing is limited to conductive objects, and the multilayer structure still requires broader deployment validation. Reviewed 2026-07-21	2026	Origami deformation transmission with capacitive normal-force, shear, and proximity sensing	normal force, shear force, contact location, conductive-object proximity	60,000 mm2 multilayer origami e-skin mounted as four curved modules on a robotic arm	Capacitance vectors decoded into load location, force magnitude, shear direction, and proximity	large-area robot skin, collision-aware human-robot interaction, multi-point touch localization	peer-reviewed
Slip-actuated bionic tactile sensing with E-textile Nature Communications: Nature Communications slip-actuated bionic tactile sensing article Tests used a specific titanium-textile interface and controlled gripper disturbances; durability and coating wear need broader deployment evidence. Reviewed 2026-07-21	2025	Tribovoltaic dynamic-DC slip sensing paired with capacitive normal-force sensing	dynamic slip, normal force, sliding direction and velocity-dependent response	Stretchable PEDOT:PSS E-textile integrated on robotic fingers	Self-powered DC slip voltage and capacitive force signals used by a feedback controller	closed-loop slip mitigation, dexterous grasp monitoring, robotic manipulation	peer-reviewed
DexSkin and high-coverage conformable robotic skin for manipulation arXiv: DexSkin high-coverage conformable robotic skin preprint Robot experiments used a parallel-jaw gripper; an angular blind spot remains, policy inputs ignore spatial structure, and grounding relies on external jumper wires. Reviewed 2026-07-21	2025	Conformable parallel-plate capacitive taxel skin with cross-instance calibration	localized normal force, distributed multi-contact patterns	Tailorable soft skin covering the dome and 294 degrees around parallel-jaw gripper fingers	Per-taxel capacitance readings and calibrated normal-force heatmaps	in-hand reorientation, elastic-band packaging, delicate object manipulation, robot learning	preprint
Full-hand tactile sensing for adaptive dexterous grasping Nature Machine Intelligence: Nature Machine Intelligence full-hand tactile sensing paper Results come from one custom hand and one task family; the controller assumes known object geometry and coverage is not complete hand or body coverage. Reviewed 2026-07-21	2025	Vision-based photometric-stereo sensing of elastomer deformation	distributed contact geometry, contact location, in-hand object pose	15-DoF anthropomorphic hand with 17 vision-based tactile sensors covering 70% of the palmar surface	Tactile images reconstructed into normal maps, contact geometry, and object-pose estimates	adaptive multi-object grasping, collision-aware replanning, dexterous manipulation	peer-reviewed
Temperature/pressure bimodal sensing and the crosstalk problem Journal of Materials Chemistry C: RSC temperature/pressure bimodal tactile sensing review This is a review rather than a single-device benchmark; crosstalk, environmental interference, interface compatibility, and long-term stability remain unresolved. Reviewed 2026-07-21	2025	Review of separate- and shared-output temperature and pressure sensor architectures and decoupling methods	pressure, temperature	Survey of flexible layered, sandwich, and stacked bimodal tactile sensors	Separate or algorithmically decoupled pressure and temperature measurements	robot tactile and thermal perception, human-machine interaction, wearable and environmental monitoring	peer-reviewed
Event-based tactile sensing for sparse, low-latency robot touch Frontiers in Neuroscience: Frontiers event-based opto-tactile skin article The proof of concept used fixed-depth single presses, did not estimate force or multi-touch, and processed trials offline. Reviewed 2026-07-21	2026	Stereo Dynamic Vision Sensors observing deformation-induced light changes in a silicone optical waveguide	contact-change events, single-touch location	Flexible silicone optical-waveguide skin viewed laterally by two DVS cameras	Sparse polarity events clustered and triangulated into two-dimensional contact positions	large-area soft-robot touch localization, low-bandwidth interactive surfaces	peer-reviewed
Large-area flexible tactile arrays for curved robot surfaces ACS Applied Electronic Materials: ACS large-area flexible tactile sensor article Published evidence covers controlled curved-surface tests; whole-robot mounting, connector and data-rate behavior, contamination, and field repair are not established. Reviewed 2026-07-21	2025	Skin-inspired rhombic-grid electrode array for spatial contact-force sensing	contact-force distribution, time-varying contact and slip, gesture trajectory	Large-area high-resolution flexible tactile array designed for curved surfaces	Spatial contact-force maps and contact-motion direction and velocity estimates	curved robotic skin, slip and gesture detection, human-machine interaction	peer-reviewed

Methodology

Source identity stays separate from editorial taxonomy

Titles, source labels, and source URLs come from the cited research records. Sensor principle, modality, form factor, output, application, evidence, and limitation fields are conservative editorial normalization by the RoboSkin.ai Editorial Team. The source remains authoritative for its own claims.

Trace normalized research organizations ->

Limitations

This index is a map, not a product benchmark

Inclusion does not imply affiliation, endorsement, commercial availability, or equivalent performance across sensors and tasks. Evidence labels describe the cited public source type, not a universal quality score. Review the original source and application conditions before making an engineering decision.

Submit a correction ->