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This chapter presents a vision-based face and gesture recognition system for human-robot interaction. By using subspace method, face and predefined hand poses are classified from the three largest skin-like regions that are segmented using YIQ color representation system. In the subspace method we consider separate eigenspaces for each class or pose. Face is recognized using pose specific subspace method and gesture is recognized using the rulebased approach whenever the combinations of three skin-like regions at a particular image frame satisfy a predefined condition. These gesture commands are sent to robot through TCP/IP wireless network for human-robot interaction. The effectiveness of this method has been demonstrated by interacting with an entertainment robot named AIBO and a humanoid robot Robovie. Human-robot symbiotic systems have been studied extensively in recent years, considering that robots will play an important role in the future welfare society [Ueno, 2001]. The use of intelligent robots encourages the view of the machine as a partner in communication rather than as a tool. In the near future, robots will interact closely with a group of humans in their everyday environment in the field of entertainment, recreation, health-care, nursing, etc. In human-human interaction, multiple communication modals such as speech, gestures and body movements are frequently used. The standard input methods, such as text input via the keyboard and pointer/location information from a mouse, do not provide a natural, intuitive interaction between humans and robots. Therefore, it is essential to create models for natural and intuitive communication between humans and robots. Furthermore, for intuitive gesture-based interaction between human and robot, the robot should understand the meaning of gesture with respect to society and culture. The ability to understand hand gestures will improve the naturalness and efficiency of human interaction with robot, and allow the user to communicate in complex tasks without using tedious sets of detailed instructions. This interactive system uses robot eye’s cameras or CCD cameras to identify humans and recognize their gestures based on face and hand poses. Vision-based face recognition systems have three major components: image processing or extracting important clues (face pose and position), tracking the facial features (related position or motion of face and hand poses), and face recognition. Vision-based face recognition system varies along a number of

The aim of this paper is to present the design and development of a safe and reliable autonomous cat toy for the purposes of entertaining pet cats when human interaction is not feasible. The proposed Autonomous Feline Entertainment Robot (AFER), an autonomous cat toy, is comprised of a table-mounted base, and a robotic arm with two linkages. The AFER Version 1(vl) has a cat-toy affixed to the end of a linkage as the end effector, while the AFER Version 2 (v2) has a passive joint with a string to which a cat toy end effector is attached. The AFER v1 has 2 Degrees of Freedom (DOF), while the AFER v2 has 3DOF, and both are actuated by servomotors interfaced with an Arduino microcontroller. In order to enable maximum functionality, the AFER is designed with multiple movement patterns or modes for play, as well as the ability to change the specific end effector of the toy. Position control was used for the motion and trajectory planning when developing the movement patterns. The interaction between AFER and two kittens has been evaluated in an experimental scenario, and the results show satisfactory and safe interactions. The AFER can be used as a model for studying effective animal-robot interactions and pet entertainment.

The application of humanoid robots has been popular in the field of healthcare and education. Amid the COVID-19 pandemic, most people are isolated at home. People in isolation are constantly looking for new entertainment activities. Therefore, entertaining robots would become people’s best partner in home isolation. In this article, the possibility of an entertainment robot for isolated people from the perspective of human factors is studied. NAO is an autonomous, programmable humanoid robot developed by the French Aldebaran Robot Company. Because of its cute appearance and ability to talk to people, we use NAO for this study. When isolated at home, parents might need to work at home and not have time to spend time with their children. A robot for children has entertaining capabilities such as playing soccer and dancing to teach soccer knowledge to children. Experimental results show that NAO can learn to search and kick a ball and dance to entertain children at home in the COVID-19 pandemic.

International audience; When we perform a collaborative task with another human, we are able to tell, to a certain extent, how things are going and more precisely if things are going well or not. This knowledge allows us to adapt our behavior. Therefore, we think it is desirable to provide robots with means to measure in real-time the Quality of the Interaction with their human partners. To make this possible, we propose a model and a set of metrics targeting the evaluation of the QoI in collaborative tasks through the measure of the human engagement and the online task effectiveness. These model and metrics have been implemented and tested within the high-level controller of an entertainment robot deployed in a mall. The first results show significant differences in the computed QoI when in interaction with a fully compliant human, a confused human and a non-cooperative one.

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&rsquo, 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&rsquo, 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 &ldquo, Buddy&rdquo, 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&rsquo, 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.

International audience; In this paper, a system to determine the emotion of a group of people via facial expression analysis is proposed for the Waseda Entertainment Robots. General models and standard methods for emotion definition and recognition are briefly described, as well as strategies for computing the group global emotion, knowing the individual emotions of group members. This work is based on Ekman's extended “Big Six” emotional model, popular in Computer Science and Affective Computing. Emotion recognition via facial expression analysis is performed with a cloud-computing based solution, using Microsoft Azure Cognitive services. First, the performances of both the Face API to detect faces, and Emotion API, to compute emotion via face expression analysis, are tested. After that, a solution to compute the emotion of a group of people has been implemented and its performances compared to human perceptions. This work presents concepts and strategies which can be generalized for applications within the scope of assistive robotics and, more broadly, affective computing, wherever it will be necessary to determine the emotion of a group of people

In recent years, there have been a number of popular robotics competitions whose intent is to advance the state of research by comparing embodied entries against one another in real time. The IEEE Humanoid application challenge is intended to broaden these by allowing more open-ended entries, with a general theme within which entrants are challenged to create the most effective application involving a humanoid robot. This year’s theme was Robot Magic, and this paper describes our first-place winning entry in the 2017 competition, running on a ROBOTIS OP2 humanoid robot. We describe the overall agent design and contributions to perception, learning, control, and representation, which together support a robust live robot magic performance.

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 piano-playing robot, the exploration of correlations among music theory, rhythm and piano keys, and eventually the research on playing skill of keyboard instrument. The piano-playing robot is capable of control linear motor, servo-motor and pneumatic devices in accordance with the notes and rhythm in order to drive the mechanical structure to proper positions for pressing the keys and generating music. The devices used for this robot are mainly crucial components produced by HIWIN Technology Corp. The design of robotic hand is based on the direction of anthropomorphic hand such that five fingers will be used for playing piano. The finger actuations include actions of finger rotation, finger pressing, and finger lifting; time required for these 3 stages must meet the requirement of rhythm. The purpose of entertainment robot can be achieved by playing electric piano with robotic hand, and we hope this research can contribute to the development of domestic entertainment music playing robots.

In this paper, we propose an emotion model with growth functions for robots. Many emotion models for robots have been developed using Neural Networks (NN), which focus on the functions of emotion recognition, control, and expression. One problem that affects these emotion models for robots is the development of a “simplified” emotion generation algorithm. Users readily lose interest in “simple” systems. Most models have attempted to generate complex emotional expressions, whereas no previous studies have considered the “growth of a robot.” Therefore, we propose a growth model for emotions based on changes in the network structure of a self-organizing map. We also applied a multilayer perceptron NN to generate more sophisticated expressions of emotion using growth functions. This model generated a similar behavior to the concept of affective change described in genetic psychology. Our results showed that this emotion model was more suitable for producing a robot with growth functions based on a psychological model.

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.

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.

Deliberate control of an entertainment robot presents a special problem in balancing the requirement for intentional behavior with the existing mechanisms for autonomous action selection. It is proposed that the intentional biasing of activation in lower-level reactive behaviors is the proper mechanism for realizing such deliberative action. In addition, it is suggested that directed intentional bias can result in goal-oriented behavior without subsuming the underlying action selection used to generate natural behavior. This objective is realized through a structure called the intentional bus. The intentional bus serves as the interface between deliberative and reactive control by realizing high-level goals through the modulation of intentional signals sent to the reactive layer. A deliberative architecture that uses the intentional bus to realize planned behavior is described. In addition, it is shown how the intentional bus framework can be expanded to support the serialization of planned behavior by shifting from direct intentional influence for plan execution to attentional triggering of a learned action sequence. Finally, an implementation of this architecture, developed and tested on Sony’s humanoid robot QRIO, is described.

In this paper we discuss two techniques to reduce the size of the acoustic model while maintaining or improving the accuracy of the recognition engine. The first technique, demiphone modeling, tries to reduce the redundancy existing in a context dependent state-clustered Hidden Markov Model (HMM). Three-state demiphones optimally designed from the triphone decision tree are introduced to drastically reduce the phone space of the acoustic model and to improve system accuracy. The second redundancy elimination technique is a more classical approach based on parameter tying. Similar vectors of variances in each HMM cluster are tied together to reduce the number of parameters. The closeness between the vectors of variances is measured using a Vector Quantizer (VQ) to maintain the information provided by the variances parameters. The paper also reports speech recognition improvements using assignment of variable number Gaussians per cluster and gender-based HMMs. The main motivation behind these techniques is to improve the acoustic model and at the same time lower its memory usage. These techniques may help in reducing memory and improving accuracy of an embedded Large Vocabulary Continuous Speech Recognition (LVCSR) application.

In order to build a heterogeneous multi-robot system that can be regarded as a primitive prototype of a future symbiotic autonomous human-robot system, this paper presents a knowledge model-based heterogeneous multi-robot system implemented by a software platform. With using frame-based knowledge representation, a knowledge model is constructed to describe the features of heterogeneous robots as well as their behaviors according to human requests. The required knowledge for constructing a heterogeneous multi-robot system can be therefore integrated in a single model and shared by robots and users. Based on the knowledge model, the heterogeneous multi-robot system is defined in the Software Platform for Agents and Knowledge Management (SPAK) by use of XML format. With the use of SPAK, the cooperative operation of heterogeneous multi-robot system can be flexibly carried out. The proposed system not only can integrate heterogeneous robots and various techniques for robots, but also can automatically perform human-robot interaction and plan robot behaviors taking into account different intelligence of robots corresponding to human requests. In this paper, an actual heterogeneous multi-robot system comprised by humanoid robots (Robovie, PINO), mobile robot (Scout) and entertainment robot dog (AIBO) is built and the effectiveness of the proposed system is verified by experiment.

Most of the recently developed robots are human friendly robots which imitate an animal or human such as entertainment robot, biomimetic robot and humanoid robot. Interest in these robots is increased because the social trend is focused on health, welfare, and graying. By these social backgrounds, robots become more human friendly and suitable or home or personal environment. The more biomimetic robots resemble living creature, the more human feels familiarity. Human feels close friendship not only when feeding a pet, but also when watching a pet having the food. Most of entertainment robots and pet robots use internal-type batteries and have a self-recharging function. Entertainment robots and pet robots with internal-type batteries are not able to operate during charging the battery. So far there have been a few robots that do not depend on an internal battery. However, they need a bulky energy conversion unit and a slug or foods as an energy source, which is not suitable for home or personal application. In this paper, we introduce a new biomimetic entertainment robot with autonomous eating functionality, called EPRO-1(Eating Pet RObot version 1). The EPRO-1 is able to eat a food (a small battery), by itself and evacuate. We describe the design concept of the autonomous eating mechanism of the EPRO-1, characteristics of sub-parts of the manufactured mechanism and its control system.

This paper introduces a new entertainment robot called ELIRO-II(Eating Lizard RObot version 2)which is a bio-mimetic quadruped walking robot with autonomous eating function. We focus on the realization of the behavior of an animal, i.e., wandering around to find food and eating food. The ELIRO-II is modeled after a lizard, which has four legs, 2-DOF waist-joint, an eye part, a mouth part and a stomach part. The effectiveness of the developed robot is shown through real experiments.

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...

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.

We propose a small biped entertainment robot prototype, Sony Dream Robot (SDR-3X) that realizes Motion Entertainment by entertaining people with its controlled dynamic motion performance. New key technologies developed for SDR-3X include the Intelligent Servo Actuator (ISA), the trine-actuator composed of a motor a built-in controller and a gear Another technology is Whole Body Coordinated Dynamic Motion Control. Both technologies realize dynamic, stable motion performance in dynamic biped walking, gymnastic motions and dancing. Human-rohot interactive performances are also described in this paper.

Numerous studies have examined entertainments robots that communicate with people, but it is difficult for robots to communicate smoothly with people. We specifically examine communication with robots based on a humorous dialogue between entertainment robots. At this time, scenarios consisting of humorous dialogue must be produced for robots to use. In this paper, we propose a system that generates humorous dialogue scenarios automatically from web news articles in real time. Japan has a traditional humorous comedy called "Manzai", a kind of standup comedy. Manzai typically consists of two comedians performing humorous dialogue. We use the Manzai metaphor in our system. Our generated Manzai scenario consists of fluffy patter and dialogue filled with misunderstanding in three parts: Introduction, Body, and Conclusion. The Introduction includes a greeting and presentation of the theme of the original web content. The Body includes component of four types used to generate funny dialogue. The Conclusion includes automatically generated riddles related to words in news from the internet. We create entertainment robots to amuse people with our generated humorous robot dialogue scenario.

In this study, we developed an emotional virtual creature that grows according to a growth function model influenced by user input. Our preceding study proposed a growth model for emotions based on changes in the network structure of a self-organizing map. We applied a multilayer perceptron neural network to generate more sophisticated emotional expressions using growth functions. This model generated behavior similar to affective change, as described in behavioral genetics. Based on the growth model for emotions, we propose a virtual creature with which a user can interact using a tablet computer. This creature resembles a bouncing ball and changes color depending on its emotion. The user can pet or tap the creature, play with it using some items, and provide it food. The creature’s actions and emotional expressions are influenced by a various stimuli from the user. We implemented the virtual creature using an Apple iPad and confirmed that the creature grew and learned various emotional expressions through user interaction.

There have been many attempts made by companies and researchers to make people feel more familiar with robots. As one example, Dance performance of Entertainment Robot could conceivably provide an event that would be seen easily in a public place. In most cases, however, programmers' and researchers' workload, if they were to attempt to program dance motions for a robot and synchronize them, would be too heavy. In addition, pre-programmed dance motion and synchronization information are useful only for one certain music and are useless for any other music input. To solve these problems, we have introduced a new system that can make a robot dance automatically with real-time music input. The system consists of two main parts: the first is a real-time beat extraction system for music; the second one is a system of dance motion for a humanoid robot. In the first part, music input is analyzed using FFT and peak-to-peak time duration in the low frequency area is computed. In the second part, the process of making and synchronizing the dance motion of the humanoid robot is described. Finally, we perform experiments to check the validity of the proposed system. Also, limitations and further work are described.

Severely disabled children have little chance of environmental and social exploration and discovery. This lack of interaction and independency may lead to an idea that they are unable to do anything by themselves. In an attempt to help children in this situation, educational robotics can offer and aid, once it can provide them a certain degree of independency in the exploration of environment. The system developed in this work allows the child to transmit the commands to a robot through myoelectric and movement sensors. The sensors are placed on the child's body so they can obtain information from the body inclination and muscle contraction, thus allowing commanding, through a wireless communication, the mobile entertainment robot to carry out tasks such as play with objects and draw. In this paper, the details of the robot design and control architecture are presented and discussed. With this system, disabled children get a better cognitive development and social interaction, balancing in a certain way, the negative effects of their disabilities.

Sony’s AIBO entertainment robot has broken all records for the number of robots sold in the shortest time period. The AIBO is an autonomous home entertainment robot with artificial intelligence. Its behavior simulates a dog’s in its ability to walk and play, with built‐in functions for emotions, instincts, learning and growth. Yet AIBO was not intended by Sony to be a dog substitute, but to further the man‐robot interaction. It has received an overwhelming response worldwide and it appears as if AIBO may be just the beginning of Sony’s home entertainment robots.

The advent of computers and the World Wide Web diversified the way in which the game of Go is played. While traditional human-to-human play still remains an important form of game play, amateur players, along with some professional players, have shifted the play domain from “off-line” club houses to “on-line” Go servers. Computer Go is an important field of study to develop a software to play Go or a Go engine. In addition to human-to-human play, a Go engine or computer intelligence to play Go adds another axis to play configuration: human-to-computer play and computer-to-computer play. These revolutions in the game of Go happened in an extremely short period of time compared to the history of the game, which is more than 4,000 years. We summarize this unavoidable change for the first time in the literature, to our knowledge, and propose a novel way to interact with the current technological advances. We present the new Human-Machine-Computer-Network Interface concept and our implementation of the machine interface with a robot arm. This Lynxmotion robotic arm named Cheonsoo-I successfully places stones on a board under the proposed architecture.

This paper describes SANCHO, a mobile robot intended to perform within crowded areas as a servant, for instance as a fair or congress host. This robot has been constructed upon a commercial platform on which a number of sensors and devices have been integrated. A software control architecture has been implemented and adapted to this particular robot, enabling it to perform in human scenarios. Among the different subsystems of the control architecture developed for SANCHO, we highlight in this paper two of the most relevant ones: the navigation component which permits the robot to navigate in a safe and robust manner within crowded and dynamic environments, and the communication component which provides different possibilities for human-robot interaction. We illustrate the performance of SANCHO through a number of experiences carried out in public shows.

In the process of developing an entertainment robot, Mon-e, we represented the robot's emotional and interactive behaviors in the form of scripts. A unified model was established to manage all the different scripts. We designed the personality profile to possess two dimensions of criteria for script selection. Emotion variable was introduced to create a variety of robot behavior according to the context. Reinforcing mechanisms of the personality profile and the emotion variable were developed.

Sustainability is one of important features to be considered in a human---agent interaction (HAI) process, because humans are unavoidably accustomed to the agents and it seems to become boredom as the agents' behaviors come to be predictable. To be clear the relationship between the sustainability and the predictability, the interaction processes between human subjects and a virtual entertainment robot with either of three different interaction models are evaluated.

In this paper we propose an Entertainment Humanoid Robot model based on Latent Semantic Analysis, that tries to exhibit an emotional behavior in the interaction with human. Latent Semantic Analysis (LSA), based on vector space allows the coding of the words semantics by specific statistical computations applied to a large corpus of text. We illustrate how the creation and the use of this emotional conceptual space can provide a framework upon which to build “Latent Semantic Behavior” because it simulates the emotionalassociative capabilities of human beings. This approach integrates traditional knowledge representation with intuitive capabilities provided by geometric and sub-symbolic information modeling. To validate the effectiveness of our approach we have simulated an Humanoid Robot Robovie-M on dInfoBots a linux based framework developed in our Mobile Robot Lab

A biomimetic entertainment robot called ELIRO-II(Eating Lizard RObot version 2) is proposed that includes an autonomous eating function based on the instinctual behavior of an animal that wanders around looking for food and eat food by itself. ELIRO-II is modeled on a lizard, with four legs, a 2-DOF waist-joint, eye part, mouth part and stomach part. Each component is also designed based on the natural world, i.e. eating food(=batteries) using a tongue, walking with a side to side swinging body motion, and stacking food in the stomach(=pack).

In this paper, we discuss what factors are important to realize an autonomous robot as a partner with humans. We believe that it is important to interact with people without boring them, using verbal and non-verbal communication channels. We have already developed autonomous robots such as AIBO and QRIO, whose behaviours are manually programmed and designed. We realized, however, that this design approach has limitations; therefore we propose a new approach,intelligence dynamics, where interacting in a real-world environment using embodiment is considered very important. There are pioneering works related to this approach from brain science, cognitive science, robotics and artificial intelligence. We assert that it is important to study the emergence of entire sets of autonomous behaviours and present our approach towards this goal.

It is an obvious trend that computer network and robot technology will more and more closely combine with each other. And the robot, especially the service robot such as house robot, entertainment robot, etc, will provide different kinds of services to the mankind. This paper introduces a Service-Oriented Network Robotic Management System (SONRMS) to coordinate and management the behaviors between robots and their users so as to provide high reliability and safety measures to users. Then SONRMS? architecture is put forward. SONRMS reliability model is described by use of Stochastic Reward Net, Reliability Block Datagram and Hierarchical Model. The influence among parameters of the system upon SONRMS reliability is analyzed in the end.

The robot technology is extending to social activities such as community work, home-use and entertainment. By combining the robot technology with the popularized public Internet, it is anticipated a new application field will come out. However, Internet, as its nature, does not permit real-time communication among robots and other systems including human operators and computers. A different approach is necessary regarding communication protocols and robot control schemes. This paper proposes the combination of the Web services technology and the autonomous robot motion generation is the proper approach. For the motion generation, we introduce the muscle-like control method, which can be applied to any kinds of robots easily with proving a variety of creature-like motions. The method is applied to gait generation of a simulated four-legged robot, and the results show that it can transit from a motion to another one smoothly. In addition, the simulated robot is controlled by the Web services over Internet for investigating the feasibility of the proposed control scheme in a real network circumstance. The result shows that the proposed method provides us smooth control of the robot, even we have overhead of Web service processes and delayed communication

This paper presents a novel system which learns how the users want to control the entertainment robot with intuitive gestures. Two major problems are focused on this paper. One is how to distinct the user intuitive gestures, another is how to make the correspondence between the gestures and the control commands. Users want to use their own gestures which are not known a priori. These gestures must be classified by the systems by themselves. After the classification, the system must interpret the user intention to the control command which the user want to input. For instance, one may use waving hand gesture as the shutdown command, and another may assign the same gesture to the different command such as turning around. The primitive systems are implemented on the entertainment robot named AIBO. AIBO recognizes the gestures which are classified using Self-creating and organizing neural network. AIBO also learns how to interpret them into its command using Q-Learning technique. Some experimental results show the feasibility of the proposed approach.

Recently, design semiosis stands out in been developing industrial goods. It is that form of product has meaning. Is changing to company's image with concept of CIPD (Corporate Identity through Product Design). Now, it is that consumer's awareness changes to side that the much wealths prefer product that have better design than product that have function. Accordingly, each company is changing to development of design putting first in product development of function putting first. Is changing by entertainment robot and so on in industrial robot for production as well as robot development purpose. Therefore, need design method of robot based on design to developed robot forward. For this, must decide basis Design from development step of robot. And need correct synthesize use subject and purpose. In this PAPER, recognize about effect of when design compares applied case and other that is not so and applied design to robot. Establish target to apply in design of small size mobile robot and consider above thing.

Music's affective computing model is an important research hotspot in computer music, which can be widely used in intelligent control, multimedia retrieval, human-machine interaction and entertainment robot. On the basis of analyzing the features of music' emotion connotation and its relation with basic audial elements, this thesis brings forward some rules on music affective computing, and then constructs the architecture of music's emotion linguistic variable and defines the emotion based on fuzzy logic and Hevner's emotion loop. Afterwards, the paper illustrates the lens model of emotional communication and its utilization in fuzzy reasoning. Lastly, research on emotion recognition of music is described based on the affective computing model.

Most of the recently developed robots are human friendly robots which imitate animals or humans such as entertainment robot, bio-mimetic robot and humanoid robot. Interest for these robots are being increased because the social trend is focused on health, welfare, and graying. Autonomous eating functionality is most unique and inherent behavior of pets and animals. Most of entertainment robots and pet robots make use of internal-type battery. Entertainment robots and pet robots with internal-type battery are not able to operate during charging the battery. Therefore, if a robot has an autonomous function for eating battery as its feeds, the robot is not only able to operate during recharging energy but also become more human friendly like pets. Here, a new autonomous eating mechanism was introduced for a bio-mimetic robot, called ELIRO- II (Eating LIzard RObot version 2). The ELIRO- II is able to find a food (a small battery), eat and evacuate by itself. This work describe sub-parts of the developed mechanism such as head-part, mouth-part, and stomach-part. In addition, control system of autonomous eating mechanism is described.

The purpose of this paper was to present the study and design idea for entertainment robot with educational purpose (IRFEE). The robot has been designed for home life considering dependability and interaction. The developed robot has three objectives - 1. Develop autonomous robot, 2. Design robot considering mobility and robustness, 3. Develop robot interface and software considering entertainment and education functionalities. The autonomous navigation was implemented by active vision based SLAM and modified EPF algorithm. The two differential wheels, the pan-tilt were designed mobility and robustness and the exterior was designed considering esthetic element and minimizing interference. The speech and tracking algorithm provided the good interface with human. The image transfer and Internet site connection is needed for service of remote connection and educational purpose.

We have proposed the robot entertainment as an application for intelligent robotics. In order to raise this application as a new industry, the platform technology called OPEN-R has been developed at first. On this platform, Sony has developed various types of robots such as quadruped robot, AIBO and humanoid robot, QRIO. In this paper, we describe the technologies used in OPEN-R, then show what has been achieved on AIBO and QRIO.

In this paper we describe the architecture that allows the modeling of an emotionally intelligent robot. We chose to implement these architectures on AIBO, which is a quadruped autonomous robot, developed by Sony. AIBO was developed as an entertainment robot with its "mind" resident on a memory stick. Our goal is to develop a new mind for a companion AIBO with a more complex personality model. The focus of this paper is on a model of personality. Taking into consideration the realities concerning an emotionally intelligent AIBO, that acts in an unpredictable and changing environment, the existing models of personality need improvement, modifications and adaptations to the current situation. Most existing personality models that are used in virtual humans and agents take into consideration three layers: personality, mood and emotions or just two: personality and emotions. We, on the other hand will try to add a new set of parameters: needs that will not constitute a new layer but together with the personality layer, a pillar for the top two layers of mood and emotions. This paper introduces the architecture that renders valuable the personality model discussed above.

This work introduces our new project, dance interaction, where we investigate design methodology or principles for realizing long-term interaction between a human and a robot. By exploiting the powerful hardware of an entertainment robot QRIO, we tackle this pretty hard problem by a repeated try and test approach. As the first attempt, we try designing by an entrainment ensemble model that to be presented in this paper. Though studies are just starting and have not matured yet, current progress and prospects for the near future are addressed.

This paper proposed a knowledge model-based method to construct a heterogeneous multi-robot system that can be regarded as a primitive prototype of a future symbiotic autonomous human-robot system. In this method, with using frame-based knowledge model, the features of heterogeneous robots as well as their behaviors according to human requests are described. The required knowledge for heterogeneous multi-robot system can be therefore integrated in a single model and shared by robots and users. Based on the knowledge model, the heterogeneous multi-robot system is defined in the software platform for agents and knowledge management (SPAK) by use of XML format. With the use of SPAK, distributed intelligent agents, tele-operation via wireless network and local robot control programs, the activities of heterogeneous multi-robot system can be flexibly carried out. In the heterogeneous multi-robot system, not only various heterogeneous robots and techniques for robots are integrated, but also human-robot interaction can be automatically performed and robot behaviors can be planned by taking into account different intelligence of robots corresponding to human requests. In this paper, an actual heterogeneous multi-robot system comprised by humanoid robots (Robovie, PINO), mobile robot (Scout) and entertainment robot dog (AIBO) is constructed in order to demonstrate the effectiveness of the proposed method

SDR-4X II is the latest prototype model, which remains a small humanoid type robot and is expanding its capabilities for the adaptability in home environment. Some of the new key technologies have been developed for SDR-4X II. The first is newly developed small robot actuators names ISA-4, the second is real-time integrated adaptive motion control. The third is a motion creating software system, which allows us to create SDR's attractive motion performances. The fourth technology is real-time real-world space perception, and the fifth is multi-modal human robot interaction. These five technologies enable to realize a capable robot that can be adapted with human in home environment. In addition, we have explored and developed entertainment applications using these technologies. A cappella chorus performances and a high-tempo dance performance are introduced as the attractive applications.

Presents a method for creating high-fidelity models of animal behavior for use in robotic systems based on a behavioral systems approach, and describes in particular how an ethological model of a domestic dog can be implemented with AIBO, the Sony entertainment robot.

International audience; MuMMER (MultiModal Mall Entertainment Robot) is a four-year, EU-funded project with the overall goal of developing a humanoid robot (SoftBank Robotics’ Pepper robot being the primary robot platform) with the social intelligence to interact autonomously and naturally in the dynamic environments of a public shopping mall, providing an engaging and entertaining experience to the general public. Using co-design methods, we will work together with stakeholders including customers, retailers, and business managers to develop truly engaging robot behaviours. Crucially, our robot will exhibit behaviour that is socially appropriate and engaging by combining speech-based interaction with non-verbal communication and human-aware navigation. To support this behaviour, we will develop and integrate new methods from audiovisual scene processing, social-signal processing, high-level action selection, and human-aware robot navigation. Throughout the project, the robot will be regularly deployed in Ideapark, a large public shopping mall in Finland. This position paper describes the MuMMER project: its needs, the objectives, R&D challenges and our approach. It will serve as reference for the robotics community and stakeholders about this ambitious project, demonstrating how a co-design approach can address some of the barriers and help in building follow-up projects.