Skip to main content
SpringerLink
Log in

An Intelligent System for Human Intent and Environment Detection Through Tactile Data

  • Conference paper
  • First Online:
Advances in System-Integrated Intelligence (SYSINT 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 546))

Included in the following conference series:

  • 1184 Accesses

Abstract

The tackled application aims at demonstrating the effectiveness of using tactile sensors for multiple purposes at the same time. In particular, tactile data are exploited for: the estimation of a wire diameter by using a previously trained classifier; teaching the robot new wire routing trajectories in case of unknown grasped wires; stopping the autonomous execution of previously learned trajectories to avoid damages due to possible wire entanglements.

This work was partially supported by the European Commission within the H2020 REMODEL Project (no. 870133).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://www.ros.org/.

  2. 2.

    http://wiki.ros.org/Services.

  3. 3.

    http://wiki.ros.org/actionlib.

References

  1. Howe, R.: Tactile sensing and control of robotic manipulation. J. Adv. Robot. 8, 245–261 (1994)

    Article  Google Scholar 

  2. De Oliveira, T.E.A., Cretu, A.M., Da Fonseca, V.P., Petriu, E.M.: Touch sensing for humanoid robots. IEEE Instrum. Meas. Mag. 18, 13–19 (2015)

    Article  Google Scholar 

  3. Jamali, N., Sammut, C.: Material classification by tactile sensing using surface textures. In: 2010 IEEE International Conference on Robotics and Automation, pp. 2336–2341 (2010)

    Google Scholar 

  4. Bandyopadhyaya, I., Babu, D., Kumar, A., Roychowdhury, J.: Tactile sensing based softness classification using machine learning. In: 2014 IEEE International Advance Computing Conference (IACC), pp. 1231–1236 (2014)

    Google Scholar 

  5. Liu, W., et al.: Discrimination of object curvature based on a sparse tactile sensor array. Micromachines 11(6), 583 (2020)

    Article  Google Scholar 

  6. Prado da Fonseca, V., Alves de Oliveira, T.E., Petriu, E.M.: Estimating the orientation of objects from tactile sensing data using machine learning methods and visual frames of reference. Sensors 19(10), 2285 (2019)

    Article  Google Scholar 

  7. Damian, D.D., Newton, T.H., Pfeifer, R., Okamura, A.M.: Artificial tactile sensing of position and slip speed by exploiting geometrical features. IEEE/ASME Trans. Mechatron. 20(1), 263–274 (2015)

    Article  Google Scholar 

  8. Stachowsky, M., Hummel, T., Moussa, M., Abdullah, H.A.: A slip detection and correction strategy for precision robot grasping. IEEE/ASME Trans. Mechatron. 21(5), 2214–2226 (2016)

    Article  Google Scholar 

  9. Costanzo, M.: Control of robotic object pivoting based on tactile sensing. Mechatronics 76, 102545 (2021)

    Article  Google Scholar 

  10. Costanzo, M., De Maria, G., Natale, C.: Two-fingered in-hand object handling based on force/tactile feedback. IEEE Trans. Rob. 36(1), 157–173 (2020)

    Article  Google Scholar 

  11. Yousef, H., Boukallel, M., Althoefer, K.: Tactile sensing for dexterous in-hand manipulation in robotics-a review. Sens. Actuators A 167(2), 171–187 (2011)

    Article  Google Scholar 

  12. Kappassov, Z., Corrales, J.-A., Perdereau, V.: Tactile sensing in dexterous robot hands - review. Robot. Auton. Syst. 74, 195–220 (2015)

    Article  Google Scholar 

  13. Lee, H.: A survey on robot teaching: categorization and brief review. Appl. Mech. Mater. 330, 648–656 (2013)

    Article  Google Scholar 

  14. Villani, V., Pini, F., Leali, F., Secchi, C., Fantuzzi, C.: Survey on human-robot interaction for robot programming in industrial applications. IFAC-PapersOnLine 51(11), 66–71 (2018)

    Article  Google Scholar 

  15. Cirillo, A., Costanzo, M., Laudante, G., Pirozzi, S.: Tactile sensors for parallel grippers: design and characterization. Sensors 21(5), 2021 (1915)

    Google Scholar 

  16. Pirozzi, S., Natale, C.: Tactile-based manipulation of wires for switchgear assembly. IEEE/ASME Trans. Mechatron. 23(6), 2650–2661 (2018)

    Article  Google Scholar 

  17. Cirillo, A., Laudante, G., Pirozzi, S.: Tactile sensor data interpretation for estimation of wire features. Electronics 10(12), 1458 (2021)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Università degli Studi della Campania “Luigi Vanvitelli”, Aversa, Caserta, Italy

    Gianluca Laudante & Salvatore Pirozzi

Authors
  1. Gianluca Laudante
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Salvatore Pirozzi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gianluca Laudante .

Editor information

Editors and Affiliations

  1. Department of Electrical, Electronic and Telecommunication Engineering and Naval Architecture (DITEN), University of Genova, Genoa, Italy

    Maurizio Valle

  2. Fraunhofer Institute for Manufacturing Technology and Advanced Materials, Bremen, Germany

    Dirk Lehmhus

  3. Department of Electrical, Electronic and Telecommunication Engineering and Naval Architecture (DITEN), University of Genova, Genoa, Italy

    Christian Gianoglio

  4. Department of Electrical, Electronic and Telecommunication Engineering and Naval Architecture (DITEN), University of Genova, Genoa, Italy

    Edoardo Ragusa

  5. Department of Electrical, Electronic and Telecommunication Engineering and Naval Architecture (DITEN), University of Genova, Genoa, Italy

    Lucia Seminara

  6. Computer Science and Mathematics, University of Bremen, Bremen, Germany

    Stefan Bosse

  7. Department of Electrical and Electronics Engineering (EEE), Lebanese International University (LIU), Beirut, Lebanon

    Ali Ibrahim

  8. BIBA, University of Bremen, Bremen, Germany

    Klaus-Dieter Thoben

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Laudante, G., Pirozzi, S. (2023). An Intelligent System for Human Intent and Environment Detection Through Tactile Data. In: Valle, M., et al. Advances in System-Integrated Intelligence. SYSINT 2022. Lecture Notes in Networks and Systems, vol 546. Springer, Cham. https://doi.org/10.1007/978-3-031-16281-7_47

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-16281-7_47

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16280-0

  • Online ISBN: 978-3-031-16281-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation