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A Robotic Skin for Collision Avoidance and Affective Touch Recognition

Dana Hughes, JOHN LAMMIE, Nikolaus Correll

Year
2018
Citations
92

Abstract

We describe a flexible robotic skin module that can measure proximity, contact and force, as well as algorithms for detecting obstacles, human hands, and affective touch gestures. The computational requirements of the proposed architecture are in line with the capabilities of a small microcontroller, allowing for a majority of the data to be processed colocated with the skin. The resulting system only communicates low-bandwidth information of interest, thereby solving challenges in routing high-bandwidth information and reducing the burden on a robot's central processing unit. We describe design and manufacturing of a 10.8 × 10.8 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> skin patch containing 64 sensors, classification results for six different affective touch gestures, and a method that allows the skin to differentiate between an approaching human hand and various obstacles.

Keywords

GestureMicrocontrollerComputer scienceBandwidth (computing)Gesture recognitionRobotArchitectureArtificial intelligenceCollision detectionHuman–computer interaction

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