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A Model-Based Sensor Fusion Approach for Force and Shape Estimation in Soft Robotics

Stefan Escaida Navarro, Steven Nagels, Hosam Alagi, Lisa-Marie Faller, Olivier Goury, Thor Morales Bieze, Hubert Zangl, Björn Hein, Raf Ramakers, Wim Deferme, Gang Zheng, Christian Duriez

Year
2020
Citations
80

Abstract

In this letter, we address the challenge of sensor fusion in Soft Robotics for estimating forces and deformations. In the context of intrinsic sensing, we propose the use of soft capacitive sensing to find a contact's location, and the use of pneumatic sensing to estimate the force intensity and the deformation. Using a FEM-based numerical approach, we integrate both sensing streams and model two Soft Robotics devices we have conceived. These devices are a Soft Pad and a Soft Finger. We show in an evaluation that external forces on the Soft Pad can be estimated and that the shape of the Soft Finger can be reconstructed.

Keywords

Soft roboticsRoboticsCapacitive sensingArtificial intelligenceSoft sensorComputer scienceContext (archaeology)Sensor fusionComputer visionDeformation (meteorology)

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