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Unlike the market slowdown of industrial robots, service & entertainment robots have been highly regarded by most robotics reseach and market research agencies. In this study we developed a music playing robot (which can also work as a service robot) for public performance. The research is mainly focused on the mechanical and electrical control of...
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... receiving information of music note and rhythm, the system will determine next targeted position for music playing based on music note information. Figure 1 is composed with anthropomorphic approach. ...
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... bending is within the bending range of 1mm steel wire. The appearance of the second generation mechanical hand is as shown in Figure 10. ...
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... the pressing action is completed, the hand will return to the normal state. The finger pressing process is simulated by computer software as shown in the following Figure 11 and Figure 12. The distance from the finger position on the white key to the finger position on the chromatic key is 30 mm, the width of chromatic key is around 8 mm, and the width of buffer silicone at finger tip is 6 mm. ...
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... the pressing action is completed, the hand will return to the normal state. The finger pressing process is simulated by computer software as shown in the following Figure 11 and Figure 12. The distance from the finger position on the white key to the finger position on the chromatic key is 30 mm, the width of chromatic key is around 8 mm, and the width of buffer silicone at finger tip is 6 mm. ...
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... the actuation of mechanism must be in a stable state such that the heights of fingers and keys will be raised by a certain distance during piano- playing on the white keys. The dimensions of the design appearance are as shown in Figure 13 and Figure 14. ...
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... the actuation of mechanism must be in a stable state such that the heights of fingers and keys will be raised by a certain distance during piano- playing on the white keys. The dimensions of the design appearance are as shown in Figure 13 and Figure 14. ...
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... devices will be integrated on one mobile joint mechanism to form a mobile joint module with the feature of the second generation mechanical hand as the third degree of freedom for playing the chromatic key. The appearance dimension of this module is as shown in Figure 15. The bottom plate of mechanical hand is integrated with the mobile joint module in order to facilitate the action of forward stretching of mobile joint. ...
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... higher speed will lead to larger impact on the mechanical hand, thus this statistic must be adjusted in accordance with the requirement of piano-playing. The dimensions of the design appearance are as shown in Figure 16. ...
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... features of maximum stress and maximum deformation among three generations of mechanical fingers have led to different statistics of increased finger load. Figure 17. The curves of structure-stress of the first generation, second generation, and third generation fingers Figure 18. ...
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... 17. The curves of structure-stress of the first generation, second generation, and third generation fingers Figure 18. The curves of structure-deformation of the first generation, second generation, and third generation fingers ...
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... on the experimental statistics of structures, stress of each load, and deformations of the first generation, second generation, and third generation mechanical fingers, curves are drawn from all points for solving the trend lines. Six linear straight lines can be obtained from Figure 17 and Figure 18 in order to obtain the estimated structures, stresses corresponding to all loads, and deformation formula corresponding to all loads of mechanical fingers. ...
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... on the experimental statistics of structures, stress of each load, and deformations of the first generation, second generation, and third generation mechanical fingers, curves are drawn from all points for solving the trend lines. Six linear straight lines can be obtained from Figure 17 and Figure 18 in order to obtain the estimated structures, stresses corresponding to all loads, and deformation formula corresponding to all loads of mechanical fingers. ...
Citations
... The production IOP Publishing doi:10.1088/1757-899X/1292/1/012015 2 of high-quality expressive performance, particularly, requires nuanced coupling between the dexterity, adaptability, and mechanical compliance of the fingers and the dynamics of the piano itself. Traditional research on piano playing have centered on the joint biodynamics [5,13] of piano strikes and their robot replica [22,27,24,26,4,17,12,21,27,16,21,25]. The piano challenge is narrowly understood either without considering the biomechanical constraint or merely via mechanically engineering a robot reproduction. ...
Over billions of years, natural lives and organs have evolved with essential self-organized life-sustaining activities such as locomotion and respiration. Biological studies have shown that the Central Pattern Generator (CPG) is the essential mechanism for such pattern transitions. Embodied intelligence is a paradigm for investigating how humans employ the decentralized controller and embodiment of the body to interact with their environment (piano). Previously piano playing robots were hard-coded to implement mechanical contact and musical generation, resulting in clumsy non-anthropomorphic keystrokes. Instead, we revisit the piano challenge by studying the biomechanical physics of the body, the self-organization of reflexive behavior, and the neuro-muscular synergy in terms of coordinated behavioral diversity and energy minimization.
... Piano playing is a challenge that is particularly interesting for humans as it requires extreme dexterity, adaptability, and behavioral richness to achieve a range of expressive playing styles [49]. A number of researchers have aimed to build both physical prototypes [50,51,52,53,54,55,56,57], data-driven virtual prototypes [49,58] and nondata-driven simulation approach [59] to manipulate this complex musical instrument. However, they have failed to mimic the biological neural and muscular activities as well as the complex passive dynamics between the interaction of a physiological-accurate body and a piano, resulting in a significant reality gap between the model and physics. ...
Understanding the coordination of multiple biomechanical degrees of freedom in biological organisms is crucial for unraveling the neurophysiological control of sophisticated motor tasks. This study focuses on the cooperative behavior of upper-limb motor movements in the context of octave playing on the piano. While the vertebrate locomotor system has been extensively investigated, the coherence and precision timing of rhythmic movements in the upper-limb system remain incompletely understood. Inspired by the spinal cord neuronal circuits (central pattern generator, CPG), a computational neuro-musculoskeletal model is proposed to explore the coordination of upper-limb motor movements during octave playing across varying tempos and volumes. The proposed model incorporates a CPG-based nervous system, a physiologically-informed mechanical body, and a piano environment to mimic human joint coordination and expressiveness. The model integrates neural rhythm generation, spinal reflex circuits, and biomechanical muscle dynamics while considering piano playing quality and energy expenditure. Based on real-world human subject experiments, the model has been refined to study tempo transitions and volume control during piano playing. This computational approach offers insights into the neurophysiological basis of upper-limb motor coordination in piano playing and its relation to expressive features.
... Previous attempts to reproduce piano playing by robots mainly focused on two aspects: the mechanical actuation of the fingers and the algorithms for finger motion planning across keys. A large variety of actuation mechanisms was proposed by using DC motors [5], servomotors [6,7], pneumatic cylinders [8,9], and tubular solenoids [10]. These actuation mechanisms were then integrated to various control and planning architectures, such as hard-coded motion paths [6], optimal path planning algorithms [5,7,10,11], and more advanced algorithms including collision avoidance [5,11]. ...
Piano is a complex instrument, which humans learn to play after many years of practice. This paper investigates the complex dynamics of the embodied interactions between a human and piano, in order to gain insights into the nature of humans’ physical dexterity and adaptability. In this context, the dynamic interactions become particularly crucial for delicate expressions, often present in advanced music pieces, which is the main focus of this paper. This paper hypothesises that the relationship between motor control for key-pressing and the generated sound is a manifold problem, with high-degrees of non-linearity in nature. We employ a minimalistic experimental platform based on a robotic arm equipped with a single elastic finger in order to systematically investigate the motor control and resulting outcome of piano sounds. The robot was programmed to run 3125 key-presses on a physical digital piano with varied control parameters. The obtained data was applied to a Gaussian Process (GP) inference modelling method, to train a network in terms of 10 playing styles, corresponding to different expressions generated by a Musical Instrument Digital Interface (MIDI). By analysing the robot control parameters and the output sounds, the relationship was confirmed to be highly nonlinear, especially when the rich expressions (such as a broad range of sound dynamics) were necessary. Furthermore this relationship was difficult and time consuming to learn with linear regression models, compared to the developed GP-based approach. The performance of the robot controller was also compared to that of an experienced human player. The analysis shows that the robot is able to generate sounds closer to humans’ in some expressions, but requires additional investigations for others.
... Jen-Chang et al. [18] designed a robot that plays the piano, which is based on a mechanical and electrical, control for them establishes a correlation of music theory, rhythm and piano keys. The hand of the robot uses five fingers to play the piano, which must be able to perform actions such as the rotation of fingers, pressure and lifting of fingers as a requirement to do the rhythm. ...
The robots are designed to help with difficult tasks for the human being, currently carried out activities that were a main feature of the human how to perform surgeries, injections, run musical instruments among others. This paper aims to highlight the Musical Artificial Intelligent and the history of the Musicians Robots.
