Large-Area Conformable Sensor for Proximity, Light Touch, and Pressure-Based Gesture Recognition

Abstract

In this paper, we present a capacitance-based sensor array for physical human-robot interaction (pHRI) applications that can measure the proximity, near-zero-force (NZF) contacts, and pressure between a robot and human body. The top segment including the electrodes is made of soft, stretchable materials, while the bottom segment consists of electrodes patterned from a thin copper film. The resulting device is soft and conformable to smooth curved surfaces of robot links while ensuring high signal integrity. It can be fabricated in different sizes from fingertips to torso because the fabrication process employs conventional, scalable methods. Using this sensor, we investigate the problem of recognizing gentle contact gestures often seen in affectionate physical interactions. The output of this multi-modal sensor is a 2D array compatible with machine learning algorithms used for pressure and image-based recognition problems. We utilize the spatio-temporal information of the 2D capacitance data by applying two existing deep neural network architectures. The highest accuracy achieved is over 99% in 7-class recognition of contact gestures involving proximity, NZF contacts, and medium pressure.