ICRA 2011 Paper Abstract


Paper WeP111.1

Silvera Tawil, David (The University of Sydney), Rye, David (The University of Sydney), Velonaki, Mari (The University of Sydney)

Touch Modality Interpretation for an EIT-Based Sensitive Skin

Scheduled for presentation during the Regular Sessions "Physical Human-Robot Interaction I" (WeP111), Wednesday, May 11, 2011, 13:40−13:55, Room 5F

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on July 5, 2020

Keywords Robot Companions and Social Human-Robot Interaction, Physical Human-Robot Interaction, Haptics and Haptic Interfaces


During social interaction, humans extract important information from tactile stimuli that improves their understanding of the interaction. The development of a similar capacity in a robot will contribute to the future success of intuitive human-robot interaction. This paper presents a method of touch sensing based on the principle of electrical impedance tomography (EIT) that can be used to implement a large, flexible and stretchable artificial sensitive skin for robots. A classifier based on the “LogitBoost” algorithm is used to classify the modality of six different types of touch on an experimental EIT-based skin. Experiments showed that the modality of touch was correctly classified in approximately 80% of the trials. This is comparable with the experimental accuracy of a human touch recipient. The classification accuracies show significant improvements from previous classification algorithms applied to different artificial sensitive skins.



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