TY - GEN
T1 - A robotic system for imitating human percussionists
AU - Sukkar, Fouad
AU - Savery, Richard
AU - Haque, Nadimul
AU - Le Gentil, Cedric
AU - Falque, Raphael
AU - Vidal-Calleja, Teresa
PY - 2023
Y1 - 2023
N2 - Robot musicians have the potential to revolutionise the way humans perceive and create music. Recent breakthroughs in this field have tended to focus more on the digital generation of music. Instead, we address how a musician’s physical embodiment can be translated to a robotic arm. Robots endowed with human-like musical capability open the possibility for wider applications such as human-robot bands, musical education and musical art. Prior work in this area tends to rely on pre-programmed actuation which is limited to simple motion and sound. In this paper, we propose a robotic system capable of imitating a human musician, with a focus on percussion instruments. Our system consists of a method for recording the human demonstration, a compact continuous representation of the demonstrated motion and a motion reproduction method which considers the dynamic constraints of the robot. We present results of our system and show that it is capable of closely reproducing the motion of the human percussionist.
AB - Robot musicians have the potential to revolutionise the way humans perceive and create music. Recent breakthroughs in this field have tended to focus more on the digital generation of music. Instead, we address how a musician’s physical embodiment can be translated to a robotic arm. Robots endowed with human-like musical capability open the possibility for wider applications such as human-robot bands, musical education and musical art. Prior work in this area tends to rely on pre-programmed actuation which is limited to simple motion and sound. In this paper, we propose a robotic system capable of imitating a human musician, with a focus on percussion instruments. Our system consists of a method for recording the human demonstration, a compact continuous representation of the demonstrated motion and a motion reproduction method which considers the dynamic constraints of the robot. We present results of our system and show that it is capable of closely reproducing the motion of the human percussionist.
UR - http://www.scopus.com/inward/record.url?scp=85184365211&partnerID=8YFLogxK
UR - https://ssl.linklings.net/conferences/acra/acra2023_proceedings/views/at_a_glance.html
UR - http://purl.org/au-research/grants/arc/DP210101336
M3 - Conference proceeding contribution
AN - SCOPUS:85184365211
T3 - Australasian Conference on Robotics and Automation, ACRA
BT - ACRA 2023 Proceedings
PB - Australian Robotics and Automation Association
T2 - 2023 Australasian Conference on Robotics and Automation, ACRA 2023
Y2 - 4 December 2023 through 6 December 2023
ER -