Model-Based Capacitive Touch Sensing in Soft Robotics: Achieving Robust Tactile Interactions for Artistic Applications
🤖 AI Summary
In soft robotic art installations, tactile sensing is severely challenged by pneumatic actuation-induced deformations, hindering robust recognition of arbitrary human hand contacts. To address this, we propose a model-driven capacitive tactile perception method. By tightly coupling SOFA-based real-time solid mechanics simulation with a capacitive sensor array, we establish a deformation-adaptive contact model that, for the first time, achieves physics-based decoupling of capacitive signals from actuation-induced artifacts—rendering the system selectively sensitive only to conductive targets (e.g., human hands). We further develop a real-time contact-point inversion algorithm enabling multi-touch localization. Evaluated on an organic soft sculpture, our approach achieves <8 mm contact localization error, stable multi-point tracking throughout dynamic deformation, and >97% detection accuracy under actuation. This work establishes a new paradigm for highly robust, high-precision, deformation-invariant tactile interaction in soft artistic robotics.
Application Category
📝 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.
Problem
Research questions and friction points this paper is trying to address.
Develops capacitive touch sensing for soft robotics.
Enables robust tactile interactions in human-robot scenarios.
Ensures selective sensitivity to human touch amidst deformations.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Capacitive touch sensor with SOFA framework
Selective sensitivity to human touch
Robust touch localization under deformation
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