Sequential clustering for tactile image compression to enable direct adaptive feedback

Andreas Geier, Gang Yan, Tito Pradhono Tomo, Shun Ogasa, Sophon Somlor, Alexander Schmitz, Shigeki Sugano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The sense of touch is often crucial for humans to perform manipulation tasks. Providing tactile feedback during teleoperation or for users of prosthetic devices would be beneficial. However, the representation of tactile information constitutes a major technical challenge, since the numerous and possibly multimodal sensor readings are massive compared to the available tactile display technology. We introduce an algorithm that deploys two stages of K-means clustering along and across tactile image frames that render tactile sensor information at each time instant. In this manner, the massive tactile information is adaptively compressed in real-time while preserving its physical meaning, thus, remains intuitive and direct. We experimentally verify and examine the characteristics of our algorithm by evaluating the original and compressed tactile data. The data was gathered during the active tactile exploration of several objects of daily living by an Allegro robot hand that was covered with 15 uSkin sensor modules providing 2403-axis force vector measurements at each time instant. Our novel algorithm is straight forward enough to be implemented into tactile feedback systems. Finally, our algorithm allows for the direct feedback of massive tactile sensor data for a broad variety of tactile sensors and tactile displays, thereby, enables the compressed yet intuitive representation of massive tactile sensor information for real-time applications.

Original languageEnglish
Title of host publication2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages8117-8124
Number of pages8
ISBN (Electronic)9781728140049
DOIs
Publication statusPublished - 2019 Nov
Event2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 - Macau, China
Duration: 2019 Nov 32019 Nov 8

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
CountryChina
CityMacau
Period19/11/319/11/8

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Geier, A., Yan, G., Tomo, T. P., Ogasa, S., Somlor, S., Schmitz, A., & Sugano, S. (2019). Sequential clustering for tactile image compression to enable direct adaptive feedback. In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 (pp. 8117-8124). [8968493] (IEEE International Conference on Intelligent Robots and Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS40897.2019.8968493