Embodied intelligence for drumming; a reinforcement learning approach to drumming robots.

Autor:	Karbasi SM; RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway.; Department of Informatics, University of Oslo, Oslo, Norway., Jensenius AR; RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway.; Department of Musicology, University of Oslo, Oslo, Norway., Godøy RI; RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway.; Department of Musicology, University of Oslo, Oslo, Norway., Torresen J; RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway.; Department of Informatics, University of Oslo, Oslo, Norway.
Jazyk:	angličtina
Zdroj:	Frontiers in robotics and AI [Front Robot AI] 2024 Nov 18; Vol. 11, pp. 1450097. Date of Electronic Publication: 2024 Nov 18 (Print Publication: 2024).
DOI:	10.3389/frobt.2024.1450097
Abstrakt:	This paper investigates the potential of the intrinsically motivated reinforcement learning (IMRL) approach for robotic drumming. For this purpose, we implemented an IMRL-based algorithm for a drumming robot called ZRob , an underactuated two-DoF robotic arm with flexible grippers. Two ZRob robots were instructed to play rhythmic patterns derived from MIDI files. The RL algorithm is based on the deep deterministic policy gradient (DDPG) method, but instead of relying solely on extrinsic rewards, the robots are trained using a combination of both extrinsic and intrinsic reward signals. The results of the training experiments show that the utilization of intrinsic reward can lead to meaningful novel rhythmic patterns, while using only extrinsic reward would lead to predictable patterns identical to the MIDI inputs. Additionally, the observed drumming patterns are influenced not only by the learning algorithm but also by the robots' physical dynamics and the drum's constraints. This work suggests new insights into the potential of embodied intelligence for musical performance. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2024 Karbasi, Jensenius, Godøy and Torresen.)
Databáze:	MEDLINE
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