Editorial: musical robotics and entertainment fueled by AI

Provisionally accepted

The convergence of robotics and artificial intelligence (AI) is revolutionizing the field of music and entertainment. The robots evolve from the execution of traditional tasks focused on services to allow an interaction advanced by the robot man (HRI) with a potential emotional commitment. The continuation of robotic expressiveness has new challenges and opportunities in the modeling, design and control of musical and entertainment robots. Current studies work mainly on the design and physical implementation of robots capable of manipulating various musical instruments \ quotes {Wang2022Data, Lim2012towards}, while the development of socially intelligent robots for HRI in real time remains under-explored . With AI progress, robots can now deal and improvise, as well as interpret and respond to human emotional states during HRI \ Cite {McColl2016survey, Wang2024human}. This research subject was initiated to present the latest developments in musical robots and entertainment for AI-Propulsénées AI. Following the call, six articles were accepted and collected in this research subject. These articles provide a complete exploration of various artistic forms, including singing, dance and musical performance on instruments such as piano, violin, guitar, drum and marimba. Figure \ Ref {Fig: Presentation} shows an overview of the musical robots studied in these studies. \ href {https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1463744/full} {Gilday et al. The piano and the choice of guitar play. Unlike existing custom robotic musical systems, the proposed hand was designed as a 3D printed structure in a single part, demonstrating an improved expressive potential in entertainment applications thanks to the modulation of mechanical properties and modes of Actuation. The study stressed that the use of system-environment interactions has enabled various multi-instrument features and variable game styles with simplified control. Instead of playing musical instruments, \ href {https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1450177/Full} {Twomey et al.} Studied the performance of Dance using soft usable soft sensors Usagables without used used sensors usable sensor usable usable usable sensors used with usable usable usables without mild portable sensor sensors portable sensors used usable usable sensor usable usable without flexible portable sensors without usable usable sensor sensors usable usable usable usable Without Soft Meaning Portable Sensors on the arm to explore if these devices could improve artistic expression. Dance movements have been modeled as colliders in mass-septing-damper virtual systems, and members’ segments were analyzed in local frames to avoid drift problems commonly associated with IMI. The authors proposed a parallel algorithm to detect improvisation dance movements and control gentle portable actuators that can change the size and lighting in response to detected movements. This work illustrated sensorimotor coordination and demonstrated how traditional dance and aesthetics could be enriched by spontaneous laptops. Learning and robot control represent one of the biggest challenges in musical and entertainment robotics, in particular to acquire manipulation skills and robotic expressiveness. \ href {https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1439629/full} {Horigoma and Shibuya} has developed a controller based on RL for a Lotin robot, Robot, a robot, a robot, a robot, a robot, a robot, a robot, a robot, a robot, a robot, a robot, a robot, a robot, a violin robot, an RL controller for a robot of Lutin, a robot, a violin robot, a violin robot, aa 7-do double-arm system activated by DC engines. The system imitates human performance with the left arm manipulating the fingers and the right arm controlling the inclination movements. The right arm regulates several parameters, including the inclination speed, the pressure, the survey point and the direction. The analysis of the target sound pressure has shown that the robot has managed to learn the violin game techniques and allows expressive performance variations. The robot was automated to play the violin according to musical scores, demonstrating its ability to interpret and perform complex musical tasks. Likewise, \ href {https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1450097/Full} {Karbasi et al. Flexible flu, which is called Zrob. They used an RL -based algorithm with a deep deterministic policy gradient architecture (DDPG), incorporating extrinsic and intrinsic reward signals. The results have shown that intrinsic awards have triggered the emergence of new rhythmic models. In addition, the physical dynamic of the robot – the intelligence clogged – was found to influence the learning algorithm due to the physical constraints of the battery configuration. This study highlights the interaction between robotic equipment and learning algorithms in achieving expressive musical performance. We can see that the learning of strengthening continues to be a powerful approach and widely used to allow robots to acquire complex manipulations and expressive skills. The above studies have studied both hardware and software progress. However, the interaction between these robots and humans has not been explored. \ href {https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1461615/Full} {Gao et al. Head and arms movements. Their study revealed that auxiliary and social gestures, in particular head movements, considerably improve temporal synchronization between humans and robots. Thanks to experiences with human participants, the results demonstrated a positive social commitment during collaboration with robots in artistic performance. The study also revealed that the gestures of the social head improved a little more synchronicity than accessory or instrumental gestures, providing quantitative information on the role of non -verbal indices in IRH. Likewise, \ href {https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1463477/full} {nishiyama and nonaka} where human participants coordinated their votes with another human or a machine (vocaloid) under non -visual conditions. The study stressed that human cooperation in human has carried out a higher similarity and anticipated synchronization in relation to human-machine interaction. These results highlight the essential role of the incarnation in the activation of natural and effective collaboration, demonstrating how physical presence and human -type features shape the dynamics of interaction. Current AI robotic systems have demonstrated the feasibility of reaching robotic expressiveness in various musical instruments. However, human-robot interaction presents a more complex subject of research which requires interdisciplinary collaboration in fields such as robotics, materials, IT, psychology, musicology, sociology and ethics.