EIT�Pneumatic Hybrid Robotic Skin for Practical and Accurate Force Map Reconstruction
Junhwi Cho, Sunggyu Bae, Junghyeon Ma, Hyosang Lee, Jung Kim, Kyungseo Park
AI summary
Problem
EIT-based robotic skin suffers from spatial sensitivity non-uniformity and unreliable absolute force magnitude, while pneumatic skin lacks contact localization; both face barriers to practical, scalable whole-body integration.
Approach
A hybrid tactile sensor fuses EIT measurements with pneumatic pressure data, applying Tikhonov-regularized reconstruction and pad-wise calibration to correct EIT artifacts and scale force estimates accurately.
Key results
- Reduced sensitivity non-uniformity (coefficient of variation dropped from 0.31 to 0.14)
- Achieved 6.9 mm average single-point contact localization error
- Demonstrated reliable multi-point contact force estimation on a humanoid robot chest
- Enabled fully 3D-printed, spray-coated fabrication for low-cost, scalable deployment
Why it matters
Provides a practical, low-cost pathway for accurate whole-body tactile sensing in real-world human-robot interaction applications.
Abstract
We present a hybrid robotic skin that combines electrical impedance tomography (EIT) with pneumatic tac- tile sensing to improve force reconstruction capability. The developed robotic skin is fabricated entirely by 3D printing and spray coating, making it affordable and easy to build. A Tikhonov-regularized inverse reconstruction, paired with per- pad pneumatic calibration, enables accurate large-area tactile sensing with a simple measurement scheme. For validation, we conducted load-cell indentation experiments; the results showed consistent force reconstruction across locations within a pad. Compared with an EIT-only baseline, sensitivity non- uniformity was also reduced, with the coefficient of variation decreasing from 0.31 to 0.14, indicating that the proposed approach addresses a longstanding limitation of EIT. We further demonstrated chest-mounted integration on a humanoid robot and found that the pneumatic signals remained reliable across diverse contact scenarios, including multiple simultane- ous contacts on the same sensing pad. These results indicate a practical path toward accurate, scalable whole-body tactile sensing in real robotic systems.