A generative physical model approach for enhancing the stroke palette for robotic drummers

Abstract

Achieving human-like musical expressivity in musical robots has been a long standing goal for roboticists and musicians who work in the emerging field of robotic musicianship. In robotic drumming, a major subfield of robotic musicianship, research towards achieving this goal focuses on the development of musical analysis and improvisational algorithms, design of robots that respond in a contextually appropriate way to music and methods to utilize gestures in collaborative music making. These research address the "what" in robotic drumming, that is, what are the notes, dynamics, inter-onset times and the rhythmic parameters that a robot would play in response to the musical analysis. Much less research has gone into "how" each of these notes are played and how to enrich the acoustical and timbral expression of robotic drummers. The main technical contribution of this work is a generative model for stroke generation in robotic drummers based on the physics of the interaction between human hand and a drumstick. A wide palette of strokes such as multiple bounce strokes, double and triple strokes can be generated using the same model by varying one single parameter, the time-varying torque applied by the thumb on the stick. A number of post processing tools have been developed to further modify the strokes produced by the physical model in an effort to simulate and capture the acoustic variety and richness of natural human drumming. We also present results from a pilot study in which 22 subjects participated in a listening test in which they listened to 10 pairs of audio files, each consisting of a human and a robotic drummer playing multiple bounce strokes. Inferential confidence interval approach was used to determine the maximum probable difference between the data obtained from the listening test and a simulated experiment in which the robotic drummer was perceptually indistinguishable from a human drummer. The results indicates that this generative physics model marks an important step towards achieving human-like musical expressivity in robotic drummers.

Brain–Machine Interfaces as Commodities: Exchanging Mind for Matter

“…Other BMI technologies use supernumerary robotics to append new, additional limbs to a person’s body in order to accomplish tasks—from lifting and grasping to travelling—more efficiently and effectively. A brain-controlled third arm has been developed and tested to enhance not only the physical dexterity of the wearer but to also develop cognitive skills such as musical rhythm (Gopinath and Weinberg 2016).…”

Robotic Arts: Current Practices, Potentials, and Implications

“…4 Refined IV consists of a mouth mechanism (lips), air supply mechanism (lung), and fingers [35]. The Robotic Drumming Prosthesis also has a generalized physical model for drum stroke generation to achieve human-like musical expressivity [36].…”

Body-Borne Computers as Extensions of Self

“…Similarly, a pair of robotic legs [55] allows the user to maneuver on extreme terrain and balance better. Georgia Tech demonstrated a three-armed drumming system [56] where the high-level control of the robotic arm is performed by brain signals and software that fine-tunes the rhythm to fit into the music being played.…”

“…A potential synergy between these fields and HCI can explore further use of such systems beyond exclusive scenarios. For example, the works presented in previous sections [44,56,62,106], showcase new setups developed in light of computer-mediated interaction. The degree of usability of such systems can be evaluated and tuned through the interaction practices and methodologies already established in HCI.…”