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Published Online: 2 June 2020

MakeSense: Automated Sensor Design for Proprioceptive Soft Robots

Publication: Soft Robotics
Volume 7, Issue Number 3

Abstract

Soft robots have applications in safe human–robot interactions, manipulation of fragile objects, and locomotion in challenging and unstructured environments. In this article, we present a computational method for augmenting soft robots with proprioceptive sensing capabilities. Our method automatically computes a minimal stretch-receptive sensor network to user-provided soft robotic designs, which is optimized to perform well under a set of user-specified deformation-force pairs. The sensorized robots are able to reconstruct their full deformation state, under interaction forces. We cast our sensor design as a subselection problem, selecting a minimal set of sensors from a large set of fabricable ones, which minimizes the error when sensing specified deformation-force pairs. Unique to our approach is the use of an analytical gradient of our reconstruction performance measure with respect to selection variables. We demonstrate our technique on a bending bar and gripper example, illustrating more complex designs with a simulated tentacle.

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Information & Authors

Information

Published In

cover image Soft Robotics
Soft Robotics
Volume 7Issue Number 3June 2020
Pages: 332 - 345
PubMed: 31891526

History

Published online: 2 June 2020
Published in print: June 2020
Published ahead of print: 9 December 2019

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Authors

Affiliations

Javier Tapia
Disney Research, Zurich, Switzerland.
Department of Computer Science, Universidad Rey Juan Carlos, Madrid, Spain.
Espen Knoop
Disney Research, Zurich, Switzerland.
Mojmir Mutný
Disney Research, Zurich, Switzerland.
Miguel A. Otaduy
Department of Computer Science, Universidad Rey Juan Carlos, Madrid, Spain.
Moritz Bächer [email protected]
Disney Research, Zurich, Switzerland.

Notes

Address correspondence to: Moritz Bächer, Disney Research, Stampfenbachstrasse 48, 8006 Zurich, Switzerland [email protected]

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This work has been supported by the projects SOMA (European Commission, Horizon 2020 Framework Programme, H2020-ICT-645599) and TouchDesign (ERC Consolidator Grant No. 772738).

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