Design and Experiment of the NAO Humanoid Robot's Plantar Tactile Sensor for Surface Classification

In order to meet the requirement of walking pattern adjustment according to the surface type, aiming at the NAO humanoid robot in this paper, a high resolution tactile sensor based on the force sensing resistor array is designed and fabricated, which can be adhered to the foot of humanoid robot. In the process of robot walking, a series of tactile images are eventually generated by processing the output signal of the tactile sensor. In addition, combined with the k-Nearest Neighbor (kNN) algorithm, a related algorithm for extracting tactile image features is designed, realizing the classification of four typical surfaces. Experiments show that when the number of robot walking steps is greater than 4, the classification accuracy can reach more than 95%.

[1]  Christoph Kayser,et al.  Texture signals in whisker vibrations. , 2006, Journal of neurophysiology.

[2]  Liang Lu,et al.  Terrain surface classification with a control mode update rule using a 2D laser stripe-based structured light sensor , 2011, Robotics Auton. Syst..

[3]  Ezzat G. Bakhoum,et al.  Resolution Enhancement Method Used for Force Sensing Resistor Array , 2015, J. Sensors.

[4]  Ole Ravn,et al.  Traversable terrain classification for outdoor autonomous robots using single 2D laser scans , 2006, Integr. Comput. Aided Eng..

[5]  Michael A. Peshkin,et al.  Multifunctional Whisker Arrays for Distance Detection, Terrain Mapping, and Object Feature Extraction , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[6]  Emmanuel G. Collins,et al.  Frequency response method for terrain classification in autonomous ground vehicles , 2008, Auton. Robots.

[7]  Véronique Perdereau,et al.  Tactile sensing in dexterous robot hands - Review , 2015, Robotics Auton. Syst..

[8]  Andreas Zell,et al.  Comparison of Different Approaches to Vibration-based Terrain Classification , 2007, EMCR.

[9]  Jonathan E. Clark,et al.  Tactile surface classification for limbed robots using a pressure sensitive robot skin , 2015, Bioinspiration & biomimetics.

[10]  W. Sardha Wijesoma,et al.  Online, self-supervised vision-based terrain classification in unstructured environments , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[11]  Shuji Hashimoto,et al.  Haptic Sensing Foot System for Humanoid Robot and Ground Recognition With One-Leg Balance , 2011, IEEE Transactions on Industrial Electronics.