Robotic Blended Sonification: Consequential Robot Sound as Creative Material for Human-Robot Interaction
CoRR(2024)
Abstract
Current research in robotic sounds generally focuses on either masking the
consequential sound produced by the robot or on sonifying data about the robot
to create a synthetic robot sound. We propose to capture, modify, and utilise
rather than mask the sounds that robots are already producing. In short, this
approach relies on capturing a robot's sounds, processing them according to
contextual information (e.g., collaborators' proximity or particular work
sequences), and playing back the modified sound. Previous research indicates
the usefulness of non-semantic, and even mechanical, sounds as a communication
tool for conveying robotic affect and function. Adding to this, this paper
presents a novel approach which makes two key contributions: (1) a technique
for real-time capture and processing of consequential robot sounds, and (2) an
approach to explore these sounds through direct human-robot interaction.
Drawing on methodologies from design, human-robot interaction, and creative
practice, the resulting 'Robotic Blended Sonification' is a concept which
transforms the consequential robot sounds into a creative material that can be
explored artistically and within application-based studies.
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