Hugging provides a sense of psychological security and is an essential form of support contributing to stress relief. Studies are being conducted to reproduce this effect using robots in human-robot interaction. In this study, we developed a prototype that acquired the user's biometric information using the huggable robot Moffuly-MS and tested its operation. The robot was equipped with a touch sensor, IMU, ultrasonic sensor, and temperature and humidity sensor. We confirmed that it was possible to use these to acquire information on the user's behavior, movements during the hug, and physiological changes. In the future, it is hoped that by improving the system's accuracy and integrating it with dialogue systems, new possibilities will be opened for stress relief and psychological care in the medical and welfare fields.

Therapeutic robots are used in facilities for older people, but many of them can only provide mechanical responses to users. To improve the quality of interactions, it is crucial to address emotional consistency. Thus, we propose Semantic Babbling, a system that enables interaction with users by utilizing the baby robot's “inner voice”. By generating inner voices and selecting babbling based on sentiment, Semantic Babbling aims to mimic infant-like responses. A crowd-sourcing survey demonstrated the significance of emotional consistency and the display of inner voice in Semantic Babbling, revealing that it improves the impression of baby robots.

As societies age rapidly, baby-sized robots using non-verbal, infant-like interactions have gained attention for their potential emotional benefits, even for users with cognitive impairments. Although occasional rough handling can disrupt natural interactions with these robots, little attention has been paid to mechanisms that recognize such behaviors and respond appropriately. To address this issue, we implemented and evaluated a function that detects rough handling using onboard inertial sensors and triggers crying sounds in a baby-sized robot. The experimental results indicated that while this crying response effectively signaled the robot’s discomfort—leading participants to perceive it as "experiencing unpleasantness"—it did not improve the impression ratings of the robot or significantly increase users’ guilt. These findings are likely influenced by the short-term, task-driven nature of the experiment, necessitating further investigation in more natural, long-term interactions.

As the loneliness problem grows more severe among older people living in nursing homes, the use of baby-like robots as companions is becoming an option to relieve this problem. However, it remains unclear how baby-like behavior affects older people. This study investigates the effect of the emotional expression of baby-like robots on older people to realize a companion robot that relieves their loneliness. Through two experiments, we investigated older adults’ impressions of one or two robots that express different emotions. They rated their impressions of the robots by watching videos of one baby-like robot that vocalized different emotional sounds (crying, laughing, or babbling) in Experiment I and two baby-like robots that vocalized different combinations of emotional sounds in Experiment II. We found that the crying robot reduced their willingness and enjoyment to interact with the robot and suppressed the emotional effects of the other robot. Our findings can help improve the well-being of older adults, providing insight into how to support older adults using baby-like robots.

This study explored a tele-operation notification interface that supports a multitasking operator independently perceiving remote information and shifting their tasks. We proposed a noise-reducing auditory notification method, which artificially replicated the cocktail party effect by decreasing the volume of the background noise and increasing the volume of visitor footsteps. Experimental results show that our proposed method provided an effective interface for operators to independently notice human presence.

Human robot interaction studies have investigated how various non-verbal expressions of robots can enhance feelings of familiarity and trust in users’ and establish good relationships between users and robots. In the field of art, this approach has been taken one step further by creating robot artworks and demonstrations through which people feel as if they are experiencing heart-to-heart communication with a robot. Although robotic behavior that conveys such a feeling is useful for human coexistence and providing a sense of security and trust, no engineering methodology can yet achieve such behavior. This study attempts to explain what kind of robot behavior is connected to such feelings by analyzing demonstrations of such a robot based on information theory. We found that the intensity of these feelings can be partially explained by transfer entropy between humans and the robot’s body movements. We expect this research to clarify how to design a robot’s behavior so that it can provide heart-to-heart communication with people as well as how to construct a robot that can build solid relationships with people in daily life.

This study investigated the influence of behavior variations in a robot-initiated greeting. Previous studies on the physical interaction between humans and robots typically focused on constructing behaviors to increase the perceived naturalness of the interaction. The specific parameters of the physical contact were of secondary interest. The experiments in our study were designed to mainly focus on the physical aspect of the robot’s interaction with the participants. We varied two parameters of our interaction, which consisted of a shoulder tap to initiate a greeting by the robot. This scenario was selected to withdraw the robot from the participant’s awareness as much as possible. The parameters were the timing of the vocal salutation as well as an optional social cue in the form of a waving motion the robot executed when the participant looked at it after the shoulder tap. The results of the experiments showed, contrary to our predictions about the influence of timing and the performance of greeting motion, that those parameters affect the perceived naturalness of the participants in no significant captivity. Our results showed that in the conducted experiments, the most influential factor on the participants was the shoulder (left or right) on which the robot tapped them.

The presence (or telepresence) feeling and virtual reality (VR) sickness affect the task execution in teleoperation. Most teleoperation works have assessed these concepts using objective (physiological signals) and subjective (questionnaires) measurements. However, these works did not include social tasks. To the best of our knowledge, there was no physiological approach in teleoperation of social tasks. We measured presence and VR sickness in a simulation of teleoperated social tasks by questionnaires and analyzed the correlation between their scores and multimodal biomarkers. The results showed some different correlations from the findings of non-teleoperation studies. These correlations were between presence and neural biomarkers in the frontal-central and central regions (for the beta and delta bands) and between VR sickness and brain biomarkers in the occipital region (for the alpha and beta bands) and the mean temperature. This work revealed significant correlations to support some biomarkers as predictors of the trend of presence and VR sickness in simulated teleoperated social tasks. These biomarkers might also be valid to predict the trend of telepresence and motion sickness in teleoperated social tasks in a remote environment.

Due to the current worldwide COVID-19 pandemic, such measures as social distancing is being promulgated to reduce community spread. Unfortunately, such steps greatly limit physical touching, and this touch starvation increases people's stress. We address this problem by focusing on touch interactions with oneself: self-touch. We developed a system that consists of a touch sensor and a supportive voice function to encourage self-touch behaviors. We experimentally evaluated whether our developed system increased self-touch behaviors and investigated its stress-buffering effects under stressful settings. The experimental results showed that the system increased self-touch behaviors, although only male participants showed significant stress-buffering effects.

Assisting patients with dementia is a significant social issue. Currently, to assist patients with dementia, a multimodal care technique called Humanitude is gaining popularity. In Humanitude, the patients are assisted through various techniques to stand up independently by utilizing their motor functions as much as possible. Humanitude care techniques encourage caregivers to increase the area of contact with patients during the sit-to-stand motion. However, Humanitude care techniques are not accurately performed by novice caregivers. Therefore, in this study, a smock-type wearable sensor was developed to measure the proximity between caregivers and care recipients during sit-to-stand motion assistance. A measurement experiment was conducted to evaluate the proximity differences between Humanitude care and simulated novice care. In addition, the effects of different care techniques on the center of mass (CoM) trajectory and muscle activity of the care recipients were investigated. The results showed that the caregivers tend to bring their top and middle trunk closer in Humanitude care compared with novice simulated care. Furthermore, it was observed that the CoM trajectory and muscle activity under Humanitude care were similar to those observed when the care recipient stands up independently. These results validate the effectiveness of Humanitude care and provide useful information for teaching techniques in Humanitude.

We propose a wearable tactile sensor suit, which can be regarded as tactile sensor networks, for monitoring natural body dynamics to be exploited as a computational resource for estimating the posture of a human or robot that wears it. We emulated the periodic motions of a wearer (a human and an android robot) using a novel sensor suit with a 9-channel fabric tactile sensor on the left arm. The emulation was conducted by using a linear regression (LR) model of sensor states as readout modules that predict the next wearer's movement using the current sensor data. Our result shows that the LR performance is comparable with other recurrent neural network approaches, suggesting that a fabric tactile sensor network can monitor the natural body motions, and further, this natural body dynamics itself can be used as an effective computational resource.

We introduce a minimal design approach to achieve a robot for interactive doll therapy. Our approach aims for positive interactions with older adults with dementia by just expressing the most basic elements of human-like features and relying on the user's imagination to supplement the missing information. Based on this approach, we developed HIRO, a baby-sized robot with abstract body representation and without face. The recorded voice of a real human infant emitted by robots enhance human-like features of the robot and then facilitate emotional interaction between older people and the robot. A field study showed that HIRO was accepted by older adults with dementia and facilitated positive interaction by stimulating their imagination.

Although it is perceivable that interpersonal touch affects recipient's impression of touch provider as well as the information relating to the provider alike, its utility in touch mediated through communication devices (virtual interpersonal touch) remains unclear to date. In this article, we report the alleviating effect of virtual interpersonal touch on social judgment. In particular, we show that virtual hug with a remote person modulates the impression of the hearsay information about an absentee. In our experiment, participants rate their impressions as well as note down their recall of information about a third person. We communicate this information through either a speaker or a huggable medium. Our results show that virtual hug reduces the negative inferences in the recalls of information about a target person. Furthermore, they suggest the potential that the mediated communication offers in moderating the spread of negative information in human community via virtual hug.

People's responses to a hypnosis intervention is diverse and unpredictable. A system that predicts user's level of susceptibility from their electroencephalography (EEG) signals can be helpful in clinical hypnotherapy sessions. In this paper, we extracted differential entropy (DE) of the recorded EEGs from two groups of subjects with high and low hypnotic susceptibility and built a support vector machine on these DE features for the classification of susceptibility trait. Moreover, we proposed a clustering-based feature refinement strategy to improve the estimation of such trait. Results showed a high classification performance in detection of subjects' level of susceptibility before and during hypnosis. Our results suggest the usefulness of this classifier in development of future Bel systems applied in the domain of therapy and healthcare.

We report results of the analyses of the effect of communication through a humanoid robot in comparison with in-person, video-chat, and speaker on frontal brain activity of older people during an storytelling experiment. Our results suggest that whereas communicating through a physically embodied medium potentially induces a significantly higher pattern of brain activation with respect to video-chat and speaker, its difference is non-significant in comparison with in-person communication. These results imply that communicating through a humanoid robot induces a pattern of brain activity in older people that is potentially similar to in-person communication. Our findings benefit researchers and practitioners in rehabilitation and elderly care facilities in search of effective means of communication with their patients to increase their involvement in the incremental steps of their treatments. Moreover, they imply the utility of brain information as a promising sensory gateway in characterization of the behavioural responses in human-robot interaction.

We propose Intimate Touch Conversation (ITC) as a new remote communication paradigm in which an individual, who is holding a telepresence humanoid, engages in a conversation-over-distance with a remote partner that is tele-operating the humanoid. We investigate the effect of this new communication paradigm on interpersonal closeness in comparison with in-person and video-chat. Our results suggest that ITC significantly enhances the feeling of interpersonal closeness, as opposed to video-chat and in-person. In addition, they show that ITC allows elderly people to find their conversation more interesting. These results imply that feeling of intimate touch that is evoked by the presence of teleoperated android enables elderly users to establish a closer relationship with their conversational partners over distance, thereby reducing their feeling of loneliness. Our findings benefit researchers and engineers in elderly care facilities in search of effective means of establishing a social relation with their elderly users to reduce their feeling of social isolation and loneliness.

We present results of a case study on effect of humanoid in comparison with voice-only communication on frontal brain activity of elderly adults. Our results indicate that use of humanoid induces an increase in frontal brain activity. Additionally, these results imply an increase in their salivary Immunoglobulin A (sIgA) Antibody, thereby suggesting physical embodiment as a potential health factor in communication with elderly individuals. Such increases in hormonal as well as frontal brain activity, as observed in healthy condition, suggest the potential that physical embodiment can offer to the solution concept of sustaining the process of cognitive decline associated with aging and its consequential diseases such as Alzheimer.

This paper hypothesized that a straddle-type vehicle (e.g., a motorcycle) would be a suitable platform for haptic human-machine interactions that elicits affective responses or positive modulations of human emotion. Based on this idea, a new human-machine interface (HMI) for a straddle-type vehicle was proposed for haptically interacting with a rider, together with other visual (design), tactile (texture and heat), and auditory features (sound). We investigated endocrine changes after playing a riding simulator with either new interactive HMI or typical HMI. The results showed, in comparison with the typical HMI, a significant decrease of salivary cortisol level was found after riding the interactive HMI. Salivary testosterone also tended to be reduced after riding the interactive HMI, with significant reduce in salivary DHEA. The results demonstrated that haptic interaction from a vehicle, as we hypothesized, can endocrinologically influence a rider and then may mitigate rider's stress and aggression.

We present a minimalist two-hidden-layer neural architecture for emotional state estimation using electroencephalogram (EEG) data. Our model introduces a new meta-parameter, referred to as reinforced gradient coefficient, to overcome the peculiar vanishing gradient behaviour, thereby enabling the network to further explore the gradient landscape. This allows our model to further reduce its deviation from expected prediction to significantly minimize its estimation error. Furthermore, it adopts a weighing step that captures the discrepancy between two consecutive predictions during training. The value of this weighing factor is learned throughout the training phase, given its positive effect on the overall prediction accuracy of the model. We validate our approach through comparative analysis of its performance in contrast with state-of-the-art techniques in the literature, using two well known EEG databases. Our model shows significant improvement on prediction accuracy of emotional states of human subjects, while maintaining a highly simple, minimalist architecture.

This pilot study reports an experiment where we introduced huggable communication media into daytime sleep in co-sleeping situation. The purpose of the experiment was to investigate whether it would improve soothing child users' sleep and how hugging experience with anthropomorphic communication media affects child's anthropomorphic impression on the media in co-sleeping. In the experiment, nursery teachers read two-year-old or five-year-old children to sleep through huggable communication media called Hugvie and asked the children to draw Hugvie before and after the reading to evaluate changes in their impressions of Hugvie. The results show the difference of sleeping behavior with and the impressions on Hugvie between the two classes. Moreover, they also showed the possibility that co-sleeping with a humanlike communication medium induces children to sleep deeply.

The present research examines how a robot's physical anthropomorphism interacts with perceived ability of robots to impact the level of realistic and identity threat that people perceive from robots and how it affects their support for robotics research. Experimental data revealed that participants perceived robots to be significantly more threatening to humans after watching a video of an android that could allegedly outperform humans on various physical and mental tasks relative to a humanoid robot that could do the same. However, when participants were not provided with information about a new generation of robots' ability relative to humans, then no significant differences were found in perceived threat following exposure to either the android or humanoid robots. Similarly, participants also expressed less support for robotics research after seeing an android relative to a humanoid robot outperform humans. However, when provided with no information about robots' ability relative to humans, then participants showed marginally decreased support for robotics research following exposure to the humanoid relative to the android robot. Taken together, these findings suggest that very humanlike robots can not only be perceived as a realistic threat to human jobs, safety, and resources, but can also be seen as a threat to human identity and uniqueness, especially if such robots also outperform humans. We also demonstrate the potential downside of such robots to the public's willingness to support and fund robotics research.

We propose a huggable communication device called Hugvie that encourages children to concentrate on listening by reducing their stress and strengthening the feeling that the storyteller is close. We observed a group of preschool children who listened to a story and conclude that Hugvie has the potential to facilitate attention on stories. This indicates its usefulness to relieve the educational problem where children show disobedient or restless behavior during class. We discuss Hugvie's effect on learning and memory and potential applications to special-needs children.

Recent results suggest that compliance and non-linearity in physical bodies of soft robots may not be disadvantageous properties with respect to control, but rather of advantage. In the context of morphological computation one could see such complex structures as potential computational resources. In this study, we implement and exploit this view point in a spine-driven quadruped robot called Kitty by using its flexible spine as a computational resource. The spine is an actuated multi-joint structure consisting of a sequence of soft silicone blocks. Its complex dynamics are captured by a set of force sensors and used to construct a closed-loop to drive the motor commands. We use simple static, linear readout weights to combine the sensor values to generate multiple gait patterns (bounding, trotting, turning behavior). In addition, we demonstrate the robustness of the setup by applying strong external perturbations in form of additional loads. The system is able to fully recover to its nominal gait patterns (which are encoded in the linear readout weights) after the perturbation has vanished.

Body Ownership Transfer (BOT) is an illusion that we feel external objects as parts of our own body that occurs when teleoperating android robots. In past studies, we have been investigating under what conditions this illusion occurs. However, past studies were only conducted with simple operation tasks such as by only moving the robot's hand. Does this illusion occur under much complex tasks such as having a conversation? What kind of conversation setting is required to invoke this illusion? In this paper, we examined how factors in social interaction affects occurrence of BOT. Participants had conversation using the teleoperated robot under different situations and teleoperation settings. The results revealed that BOT does occur by the act of having a conversation, and that conversation partner's presence and appropriate responses are necessary for enhancement of BOT.

Robot avatar systems give the feeling we share a space with people who are actually at a distant location. Since our cognitive system specializes in recognizing a human, avatars of the distant people can make us strongly feel that we share space with them, provided that their appearance has been designed to sufficiently resemble humans. In this paper, we investigate the minimal requirements of robot avatars for distant people to feel their presence. Toward this aim, we give an overview of the chronological development of Dogu̅, which are human figurines made in ancient Japan. This survey of the Dogu̅ shows that the torso, not the face, was considered the primary element for representing a human. It also suggests that some body parts can be represented in a simple form. Following the development of Dogu̅, we use a conversation task to examine what kind of body representation is necessary to feel a distant person's presence. The experimental results show that the forms for the torso and head are required to enhance this feeling, while other body parts have less impact. Finally, we summarize design considerations for communication avatars.

The purposeful action of any agent in a complex environment requires control, that is, the determination of specific sequences of values for the parameters determining the state of the agent. In recent years, it became clear that we have to extend our notion of control if we want to understand the mechanical and chemical process management of biological systems. As it turns out, the lessons we learn from this extension can be directly used in engineering—foremost in the field of robotics, but increasingly also in other areas, such as artificial life or novel types of chemical systems design. The extension we refer to includes the intrinsic dynamics of the system to be controlled as an active, even computational element of control. The employment of the physical or chemical dynamics of a system as part of the computations necessary for control is the underlying principle of the concept of morphological computation. In our use of the term “morphology” we include all aspects of a physical system, not only the shape of the agent, the geometrical combination of the body parts, but also its material properties, such as friction coefficients or parameters describing compliance. Moreover, we also consider the distribution of sensors and actuators as part of the morphology.Conventionally (and with slight oversimplification), control is understood in terms of an agent (typically the term plant is used) and a separate entity, which is the control unit and consists of a conventional digital computer. The state space of the agent is spanned by a number of parameters, which in the case of robots are mechanical in nature, but in the case of chemical cells can be densities, phase parameters, and so on. The controller possesses, via its sensors, an (at least partial) internal representation of the state of the agent at any time. In addition, the controller can change the state of the agent via some actuators. In an ideal situation, the controller exerts complete control over the agent, which means it can determine the agent's position in state space with high accuracy. In such an ideal situation, the observable behavior is the result of a conventional computation based on the internal representation of the agent in the controller. However, there is always some noise present in the dynamics of the agent. Moreover, if the model of the agent gets too complex (high-dimensional state space, high nonlinearity, noise, etc.), the required controller may be intractable. To avoid both problems, that is, to keep the agent controllable, an often followed strategy (during the design process) consists in the reduction of the number of degrees of freedom of the agent. For example, in the case of robots this is reflected by the use of rigid body parts, which are connected by high-torque servos.Control based on morphological computation pursues a different strategy. There is still a division into agent and controller. However, the controller is no longer assumed to exert complete control, and therefore the line of separation gets fuzzy. In extreme cases (e.g., mechanically driven walking machines like passive walkers [1]) this separation can even vanish completely. Morphological computation requires that the physical (chemical) dynamics of the agent be designed in such a way that the complexity of the task that is solved by the controller is minimized. This happens by outsourcing parts of the computation to the physical body (more on the precise meaning of outsourcing later). In a simple example the body dynamics of the agent provide various limit cycles, and the task of the controller is reduced to choosing the right basin of attraction and initiating jumps into it. The choice will clearly depend on the demands made by the environment and/or the prescribed task. For example, in the case of a locomoting robot the dynamics of the body implicitly take over tasks such as the stabilization of the movement pattern against small perturbations, while the controller simply has to choose an appropriate gait. Stated differently, the number of tasks to be fulfilled by the conventional controller is reduced. This reduction can be understood as an outsourcing of computation to the body, since the control problem as such (e.g., how to handle small perturbations caused by an uneven floor in the case of walking machines) is still the same. Notably, not only can a clever exploitation of the physical dynamics of an agent reduce the amount of computation to be performed by the controller, but also the information necessary for the internal representation of the agent's state is reduced. As soon as the stabilization of a movement pattern is intrinsic to the body dynamics of the moving agent, the controller only needs to know in which basin of attraction the agent actually resides. No details about positions, velocities, and so on are necessary. In consequence, the computations that remain to the controller are not necessarily full simulations of the dynamics of the agent, but relatively simple evaluations such as “If condition A is satisfied and agent resides in basin of attraction B, jump into basin C”—a task that is mastered by a simple finite state automaton.It should be emphasized that morphological computation is more than clever systems design. Our claim that computation can be outsourced to the body and not just omitted is corroborated by a recent result of Hauser et al. [3, 4]. They demonstrated that a sufficiently complex physical body equipped with a simple readout (e.g., a feed-forward neural network or even only a linear and static readout) is computationally equivalent to a conventional device almost as powerful as a Turing machine. This finding has two major implications. The first one is that computation can be outsourced to the body in a quite literal sense. The second one is relevant for the engineer's choice of the design of an agent. There is a whole spectrum of options for distributing computations between the physical dynamics of the agent and a conventional control device. It is quite plausible that the optimal choice will not be found at either end of this spectrum. As briefly mentioned in the introduction, the agents under consideration need not be classical, macroscopic robots. It is well known that chemical process management in eukariotic cells results from an interplay between molecular, supramolecular, and mesoscopic structures (e.g., membranes or the cytoskeleton) and their dynamic interaction. For an illustrative example, consider protein sorting by vesicular transport [5].Recently, simple forms of cognition and motility have been implemented in artificial systems in the laboratory; see [2]. Such systems, besides being of fundamental interest for questions concerning the origin of life as well as modern bionanoengineering, also shed light on a form of morphological control not directly visible in the macroscopic world. In the study of their dynamics, classical mechanics is replaced, or at least complemented, by statistical physics. Furthermore, collective phenomena, such as phase transitions, start to play an important role.Morphological computation can be found on a wide range of different scales in a number of different contexts. Consequently, it has attracted many scientists from various backgrounds. For example, roboticists are interested in adopting this concept to build more energy-efficient and robust robots. Biologists try to understand the functions of body parts from the viewpoint of morphology (i.e., morphofunctionality). Computational scientists aim to capture the implications a physical implementation of certain types of computation has for computational theory as a whole. Scientists in the field of medicine have been attracted by the idea of morphological computation. For example, the decrease of movement control in elderly patients can, from the viewpoint of morphological computation, be interpreted as the loss of (morpho)computational power and is not necessarily the consequence of decreasing neural activity. The cause of this loss can be found in a change of the mechanical properties of the body—a change that also alters the attractor landscape in the state space of the body. As a result of aging, this attractor landscape may become less pronounced (e.g., self-stabilization of movement patterns may become slower) and be more difficult to navigate.The interdisciplinarity of the research community suggests that morphological computation is a very general concept. On one hand, this represents a significant challenge when we try to capture the concept in a unified theory or even if we want to define the boundaries of the field itself. On the other hand, it provides us with numerous research opportunities, especially in the interdisciplinary, overlap areas of research. We believe morphological computation even has the potential to give rise to completely new fields of research. To harvest this inherent potential of our community, we organized the 2nd International Conference on Morphological Computation (http://morphcomp.org/) in September, 2011, in Venice. As one of the results of the conference we initiated this special issue. The conference committee and all invited speakers, all experts in the field, were asked to vote for their favorite submissions among the accepted abstracts. Based on this poll, we invited the corresponding authors to submit an extended journal version of their work.As a result, we have in total nine accepted articles, which provide us with a snapshot of recent research done in the context of morphological computation. Furthermore, they also point to new directions of research in the field. While some of the articles have a focus on engineering (e.g., building a series of real robots to investigate the influence of morphology on locomotion, as in Reis et al.'s article), others are oriented toward more general considerations and point to potential future research directions. One from the latter category is the submission by Herrera and Sanz. Their article illustrates impressively how morphological computation attracts an interdisciplinary audience. The background of the authors is found in the theory of emotion. They suggest linking emotions with changes in the morphology and the resulting changed functionality. For example, if the emotion of fear arises, the body changes, namely, it gets ready—either to fight or to flee. As a consequence, the body can no longer be described as a fixed dynamical system, but has to been seen as a variable dynamical structure, which changes its state of attraction (from a finite and discrete set) depending on the emotion it embodies at the moment. This approach implies a new way of looking at the embodiment in robotics and constitutes a new challenge for the design and control of such physical bodies. Although such emotion-induced changes will take place on a slower timescale than the usual movements, the control is nontrivial. The controller will have to produce discrete switches between analogue systems in a stable fashion. The authors suggest some potential control theoretical approaches; however, we might have to rethink the control approach for such systems entirely.Another article, which also belongs to the more general category of this special issue, is the one by Füchslin et al. It consists of two parts: First, it presents and discusses a formalization of the concept of morphological computation. The authors build upon the Venice definition1 given at the First International Conference on Morphological Computation. They clarify the notions of result and input, and the notion and role of a program in morphological computation. Such a formalization is helpful when one aims at a better understanding of what it means to program a morphological computation. It is often illustrated using attractor landscapes of dynamical systems. Füchslin et al. discuss also what it means if the controller (the brain) can alter the attractor landscape. They interpret, for example, training in various sport activities not as learning how to move, but learning how to bring the body into a morphology (internal tension, geometry) that is optimally suited for a given task. Based on different types of feedback between agent and controller (body and brain), they present a hierarchy of levels of morphological computation. In a second part, they present three partially ongoing case studies of systems employing morphological computation and control in different contexts. A first case study deals with exoskeletal support systems for people with movement impairments. In a second investigation, they analyze self-assembly processes from the viewpoint of morphological computation. 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As out, the use of a clever morphology can to reduce the complexity of the corresponding learning task. and in their an approach to a simple model of a However, robots that will take of morphological computation will be very and We will have to new to understand how learning can take place The learning will have to take of the and should be to the given is to the controller with the body. While this has to be done in simulations for we in the future to see of and to see in we into the physical body, we on one in that we can computation to the but on the other we There is a space we need to understand to morphological computation in that context are passive walkers all their computation place in the physical (i.e., in the mechanical of the robot and its with the While it is to see such robots completely when walking under different We also have to consider that the physical properties of the material used For example, there is a for to they as Furthermore, we will have to the of mechanical structures when they are for research is to theoretical for morphological computation. It is to have to which properties are for computation. It has been only that there has been some in this For example, it has been by Hauser et al. [3, by two different for morphological computation, that using physical can to computation is by the concept of a Turing machine. Such a is in morphological computation. Füchslin et in this special issue, a to define morphological computation. As they their relevant aspects of what one as for morphological computation, but there are processes that can be as of morphological computation but are not by their It may be necessary to define types of morphological computation in to keep computation be more the of physical processes by conventional is based on a of the physical into sequences of Füchslin et al. claim that this a of but also a such as the of extended to be difficult to capture by if one does not believe in a fundamental between conventional and morphological computation the a also is a physical theoretical considerations should clarify there are systems that one can as and and that that are computationally when using conventional connected to the theoretical is the of and were to define a of complexity for their that directly to their However, it is to more general to the complexity of computation and the One way is to from information However, we believe that new types of might even be in and article, can be for certain However, a real which has to in such a dynamic and complex as has to be to with a number of different is a for robots. This means that the morphology has to be changed to the task. We believe that real (and therefore change of some parameters or of and should include is not to provide that robots to it is only a of we have such and we believe morphological computation will from computation has a way from the first of the concept in to we are there is still to The boundaries of the field are not well a is and are However, we believe we are right in an for morphological computation as one can see in this special issue. The community of roboticists to be the concept. There is a clear in building especially with to with is in new to morphological computation. the research community morphological computation is We are looking to more results and a new of robots. the idea of morphological computation will be into a by and like to all the of this special for their and their helpful We also like to and for their support and their

The biological hypothesis of spinal engine states that locomotion is mainly achieved by the spine, while the legs may serve as assistance. Inspired by this hypothesis, a compliant, multiple degree-of-freedom, biologically-inspired spine has been embedded into a quadruped robot, named Kitty, which has no actuation on the legs. In this paper, we demonstrate how versatile behaviors (bounding, trotting, and turning) can be generated exclusively by the spine's movements through dynamical interaction between the controller, the body, and the environment, known as embodiment. Moreover, we introduce information theoretic approach to quantitatively study the spine internal dynamics and its effect on the bounding gait based on three spinal morphologies. These three morphologies differ in the position of virtual spinal joint where the spine is easier to get bent. The experimental results reveal that locomotion can be enhanced by using the spine featuring a rear virtual spinal joint, which offers more freedom for the rear legs to move forward. In addition, the information theoretic analysis shows that, according to the morphological differences of the spine, the information structure changes. The relationship between the observed behavior of the robot and the corresponding information structure is discussed in detail.

In this paper, we propose the “Doppel teleoperation system,” which isolates several physical traits from a speaker, to investigate how personal information is conveyed to others during conversation. An underlying problem on designing personality in social robots is that it remains unclear how humans judge the personalities of conversation partners. With the Doppel system, for each of the communication channels to be transferred, one can choose it in its original form or in the one generated by the system. For example, voice and body motions can be replaced by the Doppel system while preserving the speech content. This allows us to analyze the individual effects of the physical traits of the speaker and the content in the speaker's speech on the identification of personality. This selectivity of personal traits provides a useful approach to investigate which information conveys our personality through conversation. To show the potential of our system, we experimentally tested how much the conversation content conveys the personality of speakers to interlocutors without any of their physical traits. Preliminary results show that although interlocutors have difficulty identifying speakers only using conversational contents, they can recognize their acquaintances when their acquaintances are the speakers. We point out some potential physical traits to convey personality.

We introduce a simple model of human's musculoskeletal system to identify the computation that a compliant physical body can achieve. A one-joint system driven by actuation of the springs around the joint is used as a computational device to compute the temporal integration and nonlinear combination of an input signal. Only a linear and static readout unit is needed to extract the output of the computation. The results of computer simulations indicate that the network of mechanically coupled springs can emulate several nonlinear combinations which need temporal integration. The simulation with a two-joint system also shows that, thanks to mechanical connection between the joints, a distant part of a compliant body can serve as a computational device driven by the indirect input. Finally, computational capability of antagonistic muscles and information transfer through mechanical couplings are discussed.

A spiral response-cascade hypothesis is proposed to model the mechanism that enables human communication to emerge or be maintained among agents. In this hypothesis, we propose the existence of three cascades each of which indicates intrapersonal or interpersonal mutual facilitation in the formation of someone's feelings about one's communication partners and the exhibition of behaviors in communicating with them, i.e., responding. In this paper, we discuss our examination of an important part of the hypothesis, i.e., what we call an intrapersonal responding cascade, through an experiment where the gaze interactions between a participant and a communication robot were controlled not only by controlling the robot's gaze but also by signaling participants when to shift their gaze. We report that the participants' experiences in responding to the robot enable them to regard the robot as a communicative being, which partially supports the hypothesis of the intrapersonal responding cascade.

Joint attention, a process to attend to the object that the other attends to is supposed to be important for human-robot communication as well as for human-human communication. We propose an architecture for acquiring joint attention within a certain time period for realizing natural human-robot interaction. The architecture has two featured modules: a self-organizing map that makes the leaning time shorter and an automatic visual attention selector that let the agent communicate with a human synchronously. We implemented the proposed architecture in a real robot agent and found that 30 minutes was enough for acquiring joint attention with two objects. We can conclude from preliminary experiments that even if the gaze preference of the robot is different from that of the human caregiver, it can acquire joint attention.