Topological study on the design of soft strain sensors for simultaneous multi-point contact localization

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Thuruthel, TG 

Soft strain sensors have been widely used for the development of electronic skins both for robotic and wearable applications. To sense contact location on a wide surface, the standard methodology consists of square grids of strain fibers that are able to detect single contact points but fail to detect multiple ones simultaneously. To avoid such a problem, state-of-the-art technologies implement sequential sampling that isolates each sensing node, but at the cost of a lower sampling rate. This theoretical study proposes a design methodology for multi-touch detection for parallel processed grid-based strain sensors. The fundamental idea is to add diagonal grids of varying orientations on top of the standard architecture to achieve multi-touch detection. The maximum number of detectable points and the number of required strain fibers and the overall geometry of the sensor are studied along with the error introduced when trying to sense more contact points than designed for. Overall, compared with state-of-the-art design methodologies, our work provides a guideline for more efficient grid-based architectures that are able to simultaneously detect up to a fixed finite number of contact points.

4605 Data Management and Data Science, 46 Information and Computing Sciences, 40 Engineering, 4009 Electronics, Sensors and Digital Hardware, Bioengineering
Journal Title
2021 IEEE 4th International Conference on Soft Robotics, RoboSoft 2021
Conference Name
2021 IEEE 4th International Conference on Soft Robotics (RoboSoft)
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European Commission Horizon 2020 (H2020) Future and Emerging Technologies (FET) (828818)
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (860108)
This work was supported by the SHERO project, a Future and Emerging Technologies (FET) program of the European Commission (grant agreement ID 828818), and the SMART project, European Union's Horizon 2020 research and innovation under the Marie Sklodowska-Curie (grant agreement ID 860108).