On the development of a tactile sensor for fabric manipulation and classification for industrial applications

In this paper a novel multi-modal tactile sensor is presented, featuring a matrix of capacitive pressure sensors, a microphone for acoustic measurements and proximity and ambient light sensor. The sensor is fully embedded and can be easily integrated at mechanical and electrical levels with industrial grippers. Tactile sensing design has been put on the same level of additional requirements, usually overlooked in tactile sensor research, such as the mechanical interface, cable harness and robustness against continuous and repetitive operations, just to name but a few. The performances of the different sensing modalities have been assessed in a test rig for tactile sensors. Experiments have been performed in order to show the capabilities of the sensor for implementing tactile based industrial gripper control and tactile based fabric classification.

[1]  Fulvio Mastrogiovanni,et al.  Parallel Force-Position control mediated by tactile maps for robot contact tasks , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Fulvio Mastrogiovanni,et al.  A toolbox for supporting the design of large-scale capacitive tactile systems , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

[3]  Makoto Shimojo,et al.  Mechanical filtering effect of elastic cover for tactile sensor , 1997, IEEE Trans. Robotics Autom..

[4]  Giorgio Metta,et al.  Methods and Technologies for the Implementation of Large-Scale Robot Tactile Sensors , 2011, IEEE Transactions on Robotics.

[5]  Matteo Zoppi,et al.  On the Development of a Specialized Flexible Gripper for Garment Handling , 2013 .

[6]  F. Carpi,et al.  Soft dielectrics for capacitive sensing in robot skins: Performance of different elastomer types , 2015 .

[7]  Kaspar Althoefer,et al.  Tactile sensing for dexterous in-hand manipulation in robotics-A review , 2011 .

[8]  G. W. Snedecor Statistical Methods , 1964 .

[9]  Gordon Cheng,et al.  Humanoid Multimodal Tactile-Sensing Modules , 2011, IEEE Transactions on Robotics.

[10]  Giorgio Metta,et al.  A Flexible and Robust Large Scale Capacitive Tactile System for Robots , 2013, IEEE Sensors Journal.

[11]  R S Johansson,et al.  Control of fingertip forces in multidigit manipulation. , 1999, Journal of neurophysiology.

[12]  Gordon Cheng,et al.  Humanoids learn object properties from robust tactile feature descriptors via multi-modal artificial skin , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

[13]  A. Loi,et al.  Organic bendable and stretchable field effect devices for sensing applications , 2012, 2012 IEEE Sensors.

[14]  Chia-Hsien Lin,et al.  Signal processing and fabrication of a biomimetic tactile sensor array with thermal, force and microvibration modalities , 2009, 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[15]  Giulio Sandini,et al.  Tactile Sensing—From Humans to Humanoids , 2010, IEEE Transactions on Robotics.

[16]  Nawid Jamali,et al.  Majority Voting: Material Classification by Tactile Sensing Using Surface Texture , 2011, IEEE Transactions on Robotics.

[17]  Gert Kootstra,et al.  Design of a flexible tactile sensor for classification of rigid and deformable objects , 2014, Robotics Auton. Syst..

[18]  Keith Warfield,et al.  Technology readiness levels , 2016 .

[19]  Nathan F. Lepora,et al.  Active touch for robust perception under position uncertainty , 2013, 2013 IEEE International Conference on Robotics and Automation.

[20]  Aiguo Song,et al.  A Novel Texture Sensor for Fabric Texture Measurement and Classification , 2014, IEEE Transactions on Instrumentation and Measurement.