We present new developments in the improvisational robotic percussionist project, aimed at improving human-robot interaction through design, mechanics, and perceptual modeling. Our robot, named Haile, listens to live human players, analyzes perceptual aspects in their playing in real-time, and uses the product of this analysis to play along in a collaborative and improvisatory manner. It is designed to combine the benefits of computational power in algorithmic music with the expression and visual interactivity of acoustic playing. Haile's new features include an anthropomorphic form, a linear-motor based robotic arm, a novel perceptual modeling implementation, and a number of new interaction schemes. The paper begins with an overview of related work and a presentation of goals and challenges based on Haile's original design. We then describe new developments in physical design, mechanics, perceptual implementation, and interaction design, aimed at improving human-robot interactions with Haile. The paper concludes with a description of a user study, conducted in an effort to evaluate the new functionalities and their effectiveness in facilitating expressive musical human-robot interaction. The results of the study show correlation between human's and Haile's rhythmic perception as well as user satisfaction regarding Haile's perceptual and mechanical abilties. The study also indicates areas for improvement such as the need for better timbre and loudness control and more advance and responsive interaction schemes.

The paper presents the theoretical background and the design scheme for a perceptual and improvisational robotic marimba player that interacts with human musicians in a visual and acoustic manner. Informed by an evaluation of a previously developed robotic percussionist, we present the extension of our work to melodic and harmonic realms with the design of a robotic player that listens to, analyzes and improvises pitch-based musical materials. After a discussion of the motivation for the project, theoretical background and related work, we present a set of research questions followed by our hardware and software approaches designed to address these questions. The paper concludes with a description of our plans to implement and embed these approaches in the robotic marimba player that will be used in workshops and concerts.

The paper presents our approach for human-machine interaction with an anthropomorphic mechanical percussionist that can listen to live players, analyze perceptual musical aspects in real-time, and use the product of this analysis to play along in a collaborative manner. Our robot, named Haile, is designed to combine the benefits of computational power, perceptual modeling, and algorithmic music with the richness, visual interactivity, and expression of acoustic playing. We believe that when interacting with live players, Haile can facilitate a musical experience that is not possible by any other means, inspiring users to collaborate with it in novel and expressive manners. Haile can, therefore, serve a test-bed for novel forms of musical human-machine interaction, bringing perceptual aspects of computer music into the physical world both visually and acoustically.