Elastomeric sensors for 3D shape sensing
Abstract
The ADMiRE research group develops elastomeric sensors based on soft silicone with embedded capacitances arranged in a grid-like layout. External forces evoked by stretching, bending or deforming the sensors change the local capacitances. The primary goal is to develop a computer model to visualize the sensor’s 3D shape in real-time based solely on the capacitance values. Exporting the sensor’s 3D model makes it possible to incorporate the data into external workflows for e.g. prosthetic manufacturing. By combining several methodologies, such as the finite element method (FEM) and machine learning techniques we hope to develop an acceptable solution for 3D shape sensing applicable on a range of problems and objects. Challenges comprise the model’s computational complexity (impact on real-time simulations), model accuracy, and preprocessing of the sensor data.
The AICI Forum 2022 called for project abstracts, of which three are nominated as best scientific abstract. Selected abstracts are to be presented in a 10 minute timeslot. Of the three best abstracts I achieved the third place.
Peter W. Egger
Software Engineer / Data Scientist
Maker culture enthusiast and aspiring data scientist.