Model-Based Capacitive Touch Sensing in Soft Robotics: Achieving Robust Tactile Interactions for Artistic Applications

TL;DR

This work presents a capacitive tactile skin for soft robotics that remains robust to actuation-induced deformation while enabling reliable touch localization on arbitrary surfaces. By coupling mutual capacitive sensing (MuCa) with a model-based mechanical simulation in the SOFA framework, the authors map 2D touch taxels to 3D deformations and provide multitouch capabilities. They validate robustness and localization accuracy on a soft robotic sculpture, achieving average position errors of $2.6\ \mathrm{mm}$ at rest and $4.4\ \mathrm{mm}$ under deformation, and demonstrate a baseline stability under actuation with minimal false detections. The approach has immediate relevance for arts and entertainment, medical phantoms, and other domains requiring tactile interaction with deformable soft robots.

Abstract

In this paper, we present a touch technology to achieve tactile interactivity for human-robot interaction (HRI) in soft robotics. By combining a capacitive touch sensor with an online solid mechanics simulation provided by the SOFA framework, contact detection is achieved for arbitrary shapes. Furthermore, the implementation of the capacitive touch technology presented here is selectively sensitive to human touch (conductive objects), while it is largely unaffected by the deformations created by the pneumatic actuation of our soft robot. Multi-touch interactions are also possible. We evaluated our approach with an organic soft robotics sculpture that was created by a visual artist. In particular, we evaluate that the touch localization capabilities are robust under the deformation of the device. We discuss the potential this approach has for the arts and entertainment as well as other domains.

Figures (17)

• Figure 1: A visitor at the museum uses touch to explore the interactive, sensorized soft robotics piece discussed in this work.
• Figure 2: The total capacitance at each overlapping Tx and Rx is the sum of $C_{0}$ due to the initial coupling between Tx and Rx und the $\Delta C$ due to coupling through the touching human finger.
• Figure 3: (a) The MuCa Kit, proposed by Teyssier et al. teyssier2019skin (b) Our own version of the breakout board, used in this work.
• Figure 4: An example of an activation map on an $8\!\times\!8$ grid of taxels and a weighted touch position estimate $g_{w}$.
• Figure 5: (a) Electric field configuration $\vec{E}_{0}$ for the taxel at rest. (b) Electric-field configuration $\vec{E}_{\delta}$ for the taxel experiencing the effects of underlying deformation. If the distance between the electrode layer does not change, the baseline capacitances $C_{0}$ and $C_{\delta}$ are expected to be very close.