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 Orchestral 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 Orchestral 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. 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.

翻译：随着机器人进入办公室等日常空间，其产生的声音会影响人们对它们的感知。我们提出"音乐模式"（Music Mode），这是一种由艺术家和工程师共同编程实现的创新映射机制，能将机器人关节运动转化为声音，使机器人在移动时生成音乐。我们设计了两项实验来表征这种音乐增强对用户的影响。在第一项实验中，机器人执行三项任务时播放三种不同的声音映射方案。结果显示，当机器人播放音乐模式管弦乐软件时，观察者认为它更安全、更具活力、更智能、更拟人化且更讨喜。为验证第一项实验结果源于音乐模式算法本身而非单纯音乐因素，我们开展了第二项实验：机器人通过视频形式被观察者观看，执行与第一项实验相同的三项任务，但管弦乐声音或与其运动同步或随机播放。当音乐与运动同步时，参与者对机器人智能程度的评分更高。在导航、擦桌和垃圾分类任务中，使用音乐模式的机器人累计运行约两百小时，期间旁观者的评论作为嵌入式案例研究。本研究的贡献包括：（1）跨学科编舞、音乐与编程设计流程以开发真实机器人声音特征；（2）基于运动的实时声音生成技术实现；（3）两项实验与一项日常工作中运行该特征机器人的嵌入式案例研究，结果表明该特征能提升机器人的讨喜程度与感知智能。