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• Entertainment robots, as a novel personalized interaction tool, can provide a more intelligent and entertaining way for art teaching. • This article analyzes the personalized recommendation of entertainment robots in art education based on human–computer interaction and data mining. • The experimental results indicate that this model can quickly and accurately recommend suitable fine art education content for users, improving their learning effectiveness and experience. In the current digital entertainment environment, the art learning mode of human–computer interaction can effectively enhance students' interest. Entertainment robots, as a novel personalized interaction tool, can provide a more intelligent and entertaining way for art teaching. This article analyzes the personalized recommendation of entertainment robots in art education based on human–computer interaction and data mining.On the basis of collecting a large number of fine art education resources and organizing and labeling them, data mining technology is used to extract user background information and interest preferences. Information retrieval technology is used to filter out content related to user interests from the massive art education resources based on the extracted user interests. We also use recommendation algorithms to sort and personalize the recommended content based on the user's historical behavior and other user evaluations, in order to improve the accuracy of recommendation results and user satisfaction. The effectiveness and practicality of this personalized recommendation model were verified through user surveys and data analysis. The experimental results indicate that this model can quickly and accurately recommend suitable fine art education content for users, improving their learning effectiveness and experience. [ABSTRACT FROM AUTHOR]

Featured Application: Synthetic character implemented to the physically self-growing robot can be utilized as a teacher assistant for childhood education with its sympathetic communication. Robots for communication are developed extensively with an emphasis on sympathy. This study deals with the growth of character and the control of its operation. The child has time to be alone with the nature of his/her robot friend. That child can interact with other people's emotional expressions through a robot. Step by step, the robot character will grow as the child grows. Through design studies, qualitative processes such as customer experience audit, eye tracking, mental model diagrams, and semantic differences have been executed for the results. The participatory behavior research approach through user travel is mapped from the user's lead to the evidence-based design. This research considers how synthetic characteristics can be applied to the physical growth of robot toys through the product design process. With the development of robot toy "Buddy", two variations on the robot were made to achieve recognizable growth. (1) one-dimensional height scaling and (2) facial expression including the distance between two eyes on the screen. Observations represented children's reactions when "Buddy" was released with the children. As an independent synthetic character, the robot was recognized by children who had the designed function. Robots for training may require more experimentation. [ABSTRACT FROM AUTHOR]

Robots for communication are developed extensively with an emphasis on sympathy. This study deals with the growth of character and the control of its operation. The child has time to be alone with the nature of his/her robot friend. That child can interact with other people’s emotional expressions through a robot. Step by step, the robot character will grow as the child grows. Through design studies, qualitative processes such as customer experience audit, eye tracking, mental model diagrams, and semantic differences have been executed for the results. The participatory behavior research approach through user travel is mapped from the user’s lead to the evidence-based design. This research considers how synthetic characteristics can be applied to the physical growth of robot toys through the product design process. With the development of robot toy “Buddy”, two variations on the robot were made to achieve recognizable growth. (1) one-dimensional height scaling and (2) facial expression including the distance between two eyes on the screen. Observations represented children’s reactions when "Buddy" was released with the children. As an independent synthetic character, the robot was recognized by children who had the designed function. Robots for training may require more experimentation.

Recently, biomimetic robots combining the characteristics of fish robots and airship robots have been studied. In this work, we consider balloon fish robots (BFR). This paper presents our understanding of the BFR motion obtained through simulations and experimental results. The simulation of the BFR motion is based on a traveling-wave equation, defined as the product of a sine wave and quadratic curve. In this study, we derived an equation of motion for BFR and conducted an experiment to measure the thrust force. By solving the equation of motion with the Runge-Kutta method, we are able to calculate theoretical values for the propulsion velocity of BFR. We validate the simulation by comparing theoretical and experimental propulsion speed values. As a future task, we will measure BFR thrust at more parameters. [ABSTRACT FROM AUTHOR]

The dancing actions for entertainment robots are usually designed in advance and saved in a database according to the beats and rhythm of the given music. This research is devoted to developing a real-time algorithm that can detect the primary information of the music needed for the actions of entertainment robots. The computation of the proposed algorithm is very efficient and can satisfy the requirement of real-time processing by a digital signal controller. The digitized music signal is first normalized to make the algorithm robust for miscellaneous music volume. Next, the primary features of the beat for the music are extracted. Based on the extracted features, the algorithm will then identify the occurrence of beats in the music through the use of an optimized classifier. From the accumulated information of the timing for the beats, the algorithm can provide the predicted timing information of the next beat through regression analysis. The type and tempo of the given music can also be derived thereafter. The entertainment robot can thus move or dance according to the information derived by the algorithm. A graphical user interface (GUI) program in LabVIEW is also utilized to observe and verify the analysis results. In this study, the ratio for correct beat detection is greater than 90%. The prediction ratio for the correct timing of beats is over 80%, and it is 100% correct for both music type and music tempo.

This paper presents the development toward a dancing robot that can listen to and dance along with musical performances. One of the key components of this robot is the ability to modify its dance motions with varying tempos, without exceeding motor limitations, in the same way that human dancers modify their motions. In this paper, we first observe human performances with varying musical tempos of the same musical piece, and then analyze human modification strategies. The analysis is conducted in terms of three body components: lower, middle, and upper bodies. We assume that these body components have different purposes and different modification strategies, respectively, for the performance of a dance. For all of the motions of these three components, we have found that certain fixed postures, which we call keyposes, tend to be preserved. Thus, this paper presents a method to create motions for robots at a certain music tempo, from human motion at an original music tempo, by using these keyposes. We have implemented these algorithms as an automatic process and validated their effectiveness by using a physical humanoid robot HRP-2. This robot succeeded in performing the Aizu-bandaisan dance, one of the Japanese traditional folk dances, 1.2 and 1.5 times faster than the tempo originally learned, while maintaining its physical constraints. Although we are not achieving a dancing robot which autonomously interacts with varying music tempos, we think that our method has a vital role in the dancing-to-music capability. [ABSTRACT FROM PUBLISHER]

The aim of this study was to determine how the violinist robot could produce a good quality of violin sounds. We began our study with the basic physics of producing sound with a violin. We found three parameters that influenced the quality of the sound produced by the violin; the bowing force, the bowing velocity and the sounding point. In particular, the bowing force was found to be the most important parameter in producing good sounds. Furthermore, to produce such sounds, a same amount of the bowing force must be applied on the contact point between a bow and a string. However, it is hard to keep a same amount of the bowing force on the contact point due to inherent characteristics of a bow. Thus, we primarily focused on the bowing force by considering bowing a string as a spring-mass system. Then, we devised a passive damper device to offset variables in the spring-mass system that may result in changing the bowing force on the contact point. We then validated our methodology with the violinist robot, a human-like torso robot. [ABSTRACT FROM AUTHOR]

Music has long been used to strengthen bonds between humans. In our research, we develop musical coplayer robots with the hope that music may improve human-robot symbiosis as well. In this paper, we underline the importance of non-verbal, visual communication for ensemble synchronization at the start, during and end of a piece. We propose three cues for interplayer communication, and present a thereminplaying, singing robot that can detect them and adapt its play to a human flutist. Experiments with two naive flutists suggest that the system can recognize naturally occurring flutist gestures without requiring specialized user training. In addition, we show how the use of audio-visual aggregation can allow a robot to adapt to tempo changes quickly. [ABSTRACT FROM AUTHOR]

One of the most important issues in developing an entertainment robot is human-robot interaction, in which the robot is expected to learn new behaviors specified by the user. In this article we present an imitation-based mechanism to support robot learning, and use evolutionary computing to learn new behavior sequences. We also propose several advanced techniques at the task level and the computational level to evolve complex sequences. To evaluate our approach, we use it to evolve different behaviors for a humanoid robot. The results show the promise of our approach. [ABSTRACT FROM AUTHOR]

SDR-4X II is the latest prototype model of a small biped entertainment robot. It is the improved model of SDR-4X. In this paper we report on the sensing system of this robot, which is important and essential for a small biped entertainment robot which will be used in the home environment. One technology is the design of the motion sensing system, i.e. the inclination sensor system and the force sensor system which obtains the inclination of the trunk and the foot with force. Another technology is the real-world sensing system. One aspect is the touch sensing system. The robot is used in a normal home environment, so we should strongly consider the safety aspects for human. Another is the vision sensor system. The configuration and the distance image acquisition are explained. Next is the audio sensor system which obtains the sound and the voice information. The hardware system and the direction recognition are explained. These sensing systems are the key to making the biped robot walking and dynamic motion highly stable, and understanding the real-world around the robot. [ABSTRACT FROM AUTHOR]

This study presents experiments on the imitative interactions between a small humanoid robot and a user. A dynamic neural network model of a mirror system was implemented in a humanoid robot, based on the recurrent neural network model with parametric bias (RNNPB). The experiments showed that after the robot learns multiple cyclic movement patterns as embedded in the RNNPB, it can regenerate each pattern synchronously with the movements of a human who is demonstrating the corresponding movement pattern in front of the robot. Further, the robot exhibits diverse interactive responses when the user demonstrates novel cyclic movement patterns. Those responses were analyzed and categorized. We propose that the dynamics of coherence and incoherence between the robot's and the user's movements could enhance close interactions between them, and that they could also explain the essential psychological mechanism of joint attention. [ABSTRACT FROM AUTHOR]

This paper presents the role of ethological and emotional models as the basis for an architecture in support of entertainment robotic systems. Specific examples for Sony’s AIBO are presented as well as extensions related to a new humanoid robot, SDR. [Copyright &y& Elsevier]