Music Mode: Transforming Robot Movement into Music Increases Likability and Perceived Intelligence

TL;DR

This paper introduces Music Mode, a novel system that maps robot movements to music, enhancing human perceptions of safety, intelligence, and likability through experimental validation and real-world deployment.

Contribution

The paper presents an interdisciplinary design process, a technical implementation, and experimental evidence demonstrating increased robot likability and perceived intelligence.

Findings

Participants perceived robots as more safe and likable with Music Mode.

Linked movement and music increased perceived robot intelligence.

Robots operated with Music Mode for around 200 hours in real-world tasks.

Abstract

As robots enter everyday spaces like offices, the sounds they create affect how they are perceived. We present Music Mode, a novel mapping between a robot's joint motions and sounds, programmed by artists and engineers to make the robot generate music as it moves. Two experiments were designed to characterize the effect of this musical augmentation on human users. In the first experiment, a robot performed three tasks while playing three different sound mappings. Results showed that participants observing the robot perceived it as more safe, animate, intelligent, anthropomorphic, and likable when playing the Music Mode Orchestra software. To test whether the results of the first experiment were due to the Music Mode algorithm, rather than music alone, we conducted a second experiment. Here the robot performed the same three tasks, while a participant observed via video, but the Orchestra music was either linked to its movement or random. Participants rated the robots as more intelligent when the music was linked to the movement. Robots using Music Mode logged approximately two hundred hours of operation while navigating, wiping tables, and sorting trash, and bystander comments made during this operating time served as an embedded case study. This paper has both designerly contributions and engineering contributions. The contributions are: (1) an interdisciplinary choreographic, musical, and coding design process to develop a real-world robot sound feature, (2) a technical implementation for movement-based sound generation, and (3) two experiments and an embedded case study of robots running this feature during daily work activities that resulted in increased likeability and perceived intelligence of the robot.