Semi-Automatic Flute Robot and Its Acoustic Sensing
Hikari Kuriyama, Hiroaki Sonoda, Kouki Tomiyoshi, Gou Koutaki
- Year
- 2026
- Access
- Open access
Abstract
Flute performance requires mastery of complex fingering combinations and register-dependent embouchure control, particularly jet offset adjustment for low-register production. Existing haptic and semi-automated systems do not address both aspects simultaneously through mechanical actuation. To our knowledge, no prior system fully automates fingering while mechanically assisting low-register tone production without requiring embouchure control. We developed a semi-automatic flute robot with an automatic fingering mechanism: fourteen servo motors actuate all keys via wire-based and rack-and-pinion drives in response to MIDI input, enabling performers to produce complete musical pieces through airflow alone. A jet offset assist mechanism rotates the head joint by a calibrated $22^\circ$ during low-register passages, shifting the jet offset toward a low-register configuration without modifying the instrument or embouchure. Fundamental frequency estimation confirmed correct pitch production across the chromatic range (C4--C7) and during musical performance. All key and lever movements were completed within 77.50~ms, corresponding to tempo capacity exceeding standard requirements. Harmonic analysis ($Δ\mathrm{SPL} = \mathrm{SPL}_2 - \mathrm{SPL}_3$) showed a consistent increase in $Δ$SPL for all low-register notes when activated, consistent with the intended jet offset shift. Head joint rotation completed within 40.00~ms. These results demonstrate mechanical feasibility of integrating automated fingering and register-dependent jet offset assistance under controlled conditions.
Keywords
Related papers
Review and perspectives on multimodal perception, mutual cognition, and embodied execution for human–robot collaboration in Industry 5.0
Kai Ding, Qingyuan Mao, Yaqian Zhang +3 more
Robotics and Computer-Integrated Manufacturing · 2026
Towards human-centric manufacturing: Task planning under uncertainties in human–robot collaborative assembly
Yingchao You, Ze Ji, Changyun Wei
Robotics and Computer-Integrated Manufacturing · 2026
Agentic HRC: Achieving context alignment via memory for Human–Robot Collaboration
Jiahui Si, Wenchao Li, Xi Chen +4 more
Robotics and Computer-Integrated Manufacturing · 2026
Adaptive Physics-informed Transformer with Gaussian process residual compensation for inverse dynamics modeling in Human–Robot Collaboration
Rui Qian, Xi Zhang, Dongpeng Li +2 more
Robotics and Computer-Integrated Manufacturing · 2026