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Finger contact sensing and the application in dexterous hand manipulation

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Abstract

In this paper we introduce a novel contact-sensing algorithm for a robotic fingertip which is equipped with a 6-axis force/torque sensor and covered with a deformable rubber skin. The design and the sensing algorithm of the fingertip for effective contact information identification are introduced. Validation tests show that the contact sensing fingertip can estimate contact information, including the contact location on the fingertip, the direction and the magnitude of the friction and normal forces, the local torque generated at the surface, at high speed (158–242 Hz) and with high precision. Experiments show that the proposed algorithm is robust and accurate when the friction coefficient \(\le \)1. Obtaining such contact information in real-time are essential for fine object manipulation. Using the contact sensing fingertip for surface exploration has been demonstrated, indicating the advantage gained by using the identified contact information from the proposed contact-sensing method.

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Notes

  1. The work presented in this paper has been done in collaboration between King’s College London (KCL), Université Pierre et Marie Curie (UPMC) and Shadow Robot Company (Shadow) within the HANDLE project (grant agreement ICT 231640). KCL has contributed on the fingertip contact sensing algorithm, Shadow has contributed in the fingertip design and fabrication and UPMC has contributed on the finger force feedback control and the object surface exploration using the contact information identified by the fingertip. The object pose estimation using the finger has been done by KCL with contribution from UPMC.

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Acknowledgments

This research received support provided by the HANDLE project funded by the European Commission within the Seventh Framework Programme FP7 (FP7/2007-2013) under Grant Agreement ICT 231640.

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Authors and Affiliations

  1. Department of Informatics, Centre for Robotics Research, King’s College London, London, UK

    Hongbin Liu, Joao Bimbo, Junghwan Back, Lakmal D. Seneviratne & Kaspar Althoefer

  2. Université Pierre et Marie Curie, Paris 6, France

    Kien Cuong Nguyen & Véronique Perdereau

  3. Shadow Robot Company, London, UK

    Matthew Godden

  4. Khalifa University, Abu Dhabi, United Arab Emirates

    Lakmal D. Seneviratne

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  1. Hongbin Liu
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Correspondence to Hongbin Liu.

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Liu, H., Nguyen, K.C., Perdereau, V. et al. Finger contact sensing and the application in dexterous hand manipulation. Auton Robot 39, 25–41 (2015). https://doi.org/10.1007/s10514-015-9425-4

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