Emotional Robot Research Articles

Evidence and Deployment-Based Research into Care for the Elderly Using Emotional Robots

Global aging, particularly in Japan and Europe, an associated shortage of qualified healthcare personnel, and a general preference for living at home, have all sparked an interest in the possibilities offered by robot therapy in improving quality of life. To date, however, both evidence-based research and psychological theory building on whether, and if so how and why, robots can influence the life of the elderly are rather sparse and scattered across many scientific disciplines and countries. The present paper argues in favor of a psychological, cross-cultural framework for evidence-based analyses of emotional robots. Against the background of this framework, we present building blocks for an evidence-based approach to the assessment of emotional robots and discuss interactions between evidence- and deployment-based research.

Emotional Robots

As societies age overall, there will necessarily be a significant increase of those over 80 as well as an increase in people with dementia. We know that loneliness increases with old age, and those living with dementia are particularly at risk of social isolation. Also in advanced old age opportunities for sensory stimulation and engagement in pleasurable activities are reduced. The question is which technologies can be used to extend the range of available interventions that can enhance well-being under these circumstances. Emotional robots have been developed for activity and therapeutic purposes. This article explores the experiences with the emotional robot Paro in Denmark, Germany, and the UK, and provides principles of this robot as an activity or as a therapeutic activity.

Robot Emotion and Performance Regulation Based on HMM

This paper discusses the transference process of emotional states driven by psychological energy in the active field state space and also builds a robot expression model based on the Hidden Marov Models(HMM). Facial expressions and behaviours are two important channels for human-robot interaction. Robot performance based on a static emotional state cannot vividly display dynamic and complex emotional transference. Building a real-time emotional interactive model is a critical part of robot expression. First, the attenuating emotional state space is defined and the state transfer probability is acquired. Secondly, the emotional expression model based on the HMM is proposed and the performance transference probability is calculated. Finally, this model is verified by a 15 degrees of freedom robot platform. Moreover, the interactive effects are analysed by a statistical algorithm. The experimental results demonstrate that the emotional expression model can acquire an expressive performance and remove the mechanized interactive mode when compared to traditional algorithms.

Determination of Active Personal Space Based on Emotion when Interacting with a Service Robot

This paper focuses on the determination of active personal space (APS) for a service robot based on emotional status. This is required for human-robot interaction at ease. Here, APS means the active distance (relative distance during interaction and action) between the robot and the human. APS is a function of emotion both in the human and in the robot. The other factors which are considered here are age, height, familiarity with robot, and relative motion between robot and human. According to these factors, the changes in APS are shown with graphs. During the experiments two robot emotions are considered: normal and angry. The causes of variation of APS based on the two modes are also explained.

Mathematical Models of Emotional Robots with a Non-Absolute Memory

In this paper, we discuss questions of creating an electronic intellectual analogue of a human being. We introduce a mathematical concept of stimulus generating emotions. We also introduce a definition of logical thinking of robots and a notion of efficiency coefficient to describe their efficiency of rote (mechanical) memorizing. The paper proves theorems describing properties of permanent conflicts between logical and emotional thinking of robots with a nonabsolute rote memory.

Synthetic Emotions for Humanoids

The recognition and display of synthetic emotions in humanoid robots is a critical attribute for facilitating natural human-robot interaction. The authors utilize an efficient algorithm to estimate the mood in acoustic music, and then use the results of that algorithm to drive movement generation systems to provide motions for the robot that are suitable for the music. This system is evaluated on multiple sets of humanoid robots to determine if the choice of robot platform or number of robots influences the perceived emotional content of the motions. Their tests verify that the authors’ system can accurately identify the emotional content of acoustic music and produce motions that convey a similar emotion to that in the audio. They also determine the perceptual effects of using different sized or different numbers of robots in the motion performances.

It’s not all written on the robot’s face

Past work on creating robots that can make convincing emotional expressions has concentrated on the quality of those expressions, and on assessing people’s ability to recognize them in neutral contexts, without any strong emotional valence. It would be interesting to find out whether observers’ judgments of the facial cues of a robot would be affected by a surrounding emotional context. This paper takes its inspiration from the contextual effects found on our interpretation of the expressions on human faces and computer avatars, and looks at the extent to which they also apply to the interpretation of the facial expressions of a mechanical robot head. The kinds of contexts that affect the recognition of robot emotional expressions, the circumstances under which such contextual effects occur, and the relationship between emotions and the surrounding situation, are observed and analyzed. Design implications for believable emotional robots are drawn.

Expressing Emotions in Social Robotics - A Schematic Overview Concerning the Mechatronics Aspects and Design Concepts

Facial features play an important role in expressing emotional state. Therefore, rendering realistic facial expressions plays an important role in the development of social robots within HRI. Hence, the design solutions must meet these requirements. Often mechatronic and design solutions poorly chosen can lead to unsatisfactory results. In this paper, a schematic overview concerning the design solutions adopted in the development of social robots is presented.

Toward Speech and Nonverbal Behaviors Integration for Humanoid Robot

It is essential to integrate speeches and nonverbal behaviors for a humanoid robot in human-robot interaction. This paper presents an approach using multi-object genetic algorithm to match the speeches and behaviors automatically. Firstly, with humanoid robot's emotion status, we construct a hierarchical structure to link voice characteristics and nonverbal behaviors. Secondly, these behaviors corresponding to speeches are matched and integrated into an action sequence based on genetic algorithm, so the robot can consistently speak and perform emotional behaviors. Our approach takes advantage of relevant knowledge described by psychologists and nonverbal communication. And from experiment results, our ultimate goal, implementing an affective robot to act and speak with partners vividly and fluently, could be achieved.

Emotional Interaction with a Robot Using Facial Expressions, Face Pose and Hand Gestures

Facial expression is one of the major cues for emotional communications between humans and robots. In this paper, we present emotional human robot interaction techniques using facial expressions combined with an exploration of other useful concepts, such as face pose and hand gesture. For the efficient recognition of facial expressions, it is important to understand the positions of facial feature points. To do this, our technique estimates the 3D positions of each feature point by constructing 3D face models fitted on the user. To construct the 3D face models, we first construct an Active Appearance Model (AAM) for variations of the facial expression. Next, we estimate depth information at each feature point from frontal- and side-view images. By combining the estimated depth information with AAM, the 3D face model is fitted on the user according to the various 3D transformations of each feature point. Self-occlusions due to the 3D pose variation are also processed by the region weighting function on the normalized face at each frame. The recognized facial expressions - such as happiness, sadness, fear and anger - are used to change the colours of foreground and background objects in the robot displays, as well as other robot responses. The proposed method displays desirable results in viewing comics with the entertainment robots in our experiments.

Editorial for the Special Section on Ethics and Affective Computing

Editorial for the Special Section on Ethics and Affective Computing

Are Emotional Robots Deceptive?

A common objection to the use and development of “emotional” robots is that they are deceptive. This intuitive response assumes 1) that these robots intend to deceive, 2) that their emotions are not real, and 3) that they pretend to be a kind of entity they are not. We use these criteria to judge if an entity is deceptive in emotional communication (good intention, emotional authenticity, and ontological authenticity). They can also be regarded as “ideal emotional communication” conditions that saliently operate as presuppositions in our communications with other entities. While the good intention presupposition might be a bias or illusion we really need for sustaining the social life, in the future we may want to dispense with the other conditions in order to facilitate cross-entity communication. What we need instead are not “authentic” but appropriate emotional responses-appropriate to relevant social contexts. Criteria for this cannot be given a priori but must be learned-by humans and by robots. In the future, we may learn to live with “emotional” robots, especially if our values would change. However, contemporary robot designers who want their robots to receive trust from humans had better take into account current concerns about deception and create robots that do not evoke the three-fold deception response.

On Realizing a Multi-Agent Emotion Engine

Emotions have always been a complex phenomenon and research on their causes and effects have been fraught with debates. Though a reasonable and unified theory seems lacking, there have been many attempts at building models that emote. This paper describes a multi-agent approach that aids robot emotion. Emotions are grounded on percepts from sensors and generated by dedicated emotion agents that work concurrently with others – the positive suppressing the negative and vice versa while stimulating their own kinds. Each agent forms a metaphor of an emotion-generating entity that has a replenishing capability. Both the replenishing of an emotion resource and the sampling of the environment are based on fuzzy logic. Sampling of the percepts from the sensors is based on an adrenaline-like effect. Stimulations, suppressions, emotion resource, and a look-back before decay feature embed a deep and dynamic emotional milieu into a machine. The paper presents and discusses how three emotions churned from percepts gathered by a robot act as an emotional control juice capable of governing the manner of its motion along a path.

Personal Preference Analysis for Emotional Behavior Response of Autonomous Robot in Interactive Emotion Communication

Robots must understand human intention flexibly before the two can live together, for example. Interaction Emotion Communication (IEC), bidirectional communication based on emotional behavior between human beings and robots, raises the personal affinity a robot has for human beings. IEC consists of three processes – (1) recognizing human emotion, (2) generating robot emotion, and (3) expressing robot emotion. We focus here on generating robot emotion. Emotional behavior patterns desirable in a robot vary with the person, so we also conducted individual preference analysis of emotional behavior.

A new method for face detection in colour images for emotional bio-robots

Emotional bio-robots have become a hot research topic in last two decades. Though there have been some progress in research, design and development of various emotional bio-robots, few of them can be used in practical applications. The study of emotional bio-robots demands multi-disciplinary co-operation. It involves computer science, artificial intelligence, 3D computation, engineering system modelling, analysis and simulation, bionics engineering, automatic control, image processing and pattern recognition etc. Among them, face detection belongs to image processing and pattern recognition. An emotional robot must have the ability to recognize various objects, particularly, it is very important for a bio-robot to be able to recognize human faces from an image. In this paper, a face detection method is proposed for identifying any human faces in colour images using human skin model and eye detection method. Firstly, this method can be used to detect skin regions from the input colour image after normalizing its luminance. Then, all face candidates are identified using an eye detection method. Comparing with existing algorithms, this method only relies on the colour and geometrical data of human face rather than using training datasets. From experimental results, it is shown that this method is effective and fast and it can be applied to the development of an emotional bio-robot with further improvements of its speed and accuracy.

Communication of Emotion in Social Robots through Simple Head and Arm Movements

Understanding how people perceive robot gestures will aid the design of robots capable of social interaction with humans. We examined the generation and perception of a restricted form of gesture in a robot capable of simple head and arm movement, referring to point-light animation and video experiments in human motion to derive our hypotheses. Four studies were conducted to look at the effects of situational context, gesture complexity, emotional valence and author expertise. In Study 1, four participants created gestures with corresponding emotions based on 12 scenarios provided. The resulting gestures were judged by 12 participants in a second study. Participants’ recognition of emotion was better than chance and improved when situational context was provided. Ratings of lifelikeness were found to be related to the number of arm movements (but not head movements) in a gesture. In Study 3, five novices and five puppeteers created gestures conveying Ekman’s six basic emotions which were shown to 12 Study 4 participants. Puppetry experience improved identification rates only for the emotions of fear and disgust, possibly because of limitations with the robot’s movement. The results demonstrate the communication of emotion by a social robot capable of only simple head and arm movement.

Construction of a Robot Emotion Decision-making Model Based on Tasks

To make communication more natural between robot and human,a robot emotion decision-making model based on tasks is proposed,and a mapping from multiple perception inputs to multiple behavior outputs is established.The PAD(pleasure-arousal-dominance) emotion space description considering individual factors is applied to describing the robot emotion.Based on normal distribution prototype,the behavior mapping mode combining probability with emotion is adopted so that the decision variables of decision-making model are influenced by random factors and emotion factors,which ensures the output behaviors to accord with human emotion variation.The experiment results on the Fuwa robot platform verify the validity and practicality of the method.

Young children's emotion and role recognition of teacher assistive robot in a kindergarten

Young children's emotion and role recognition of teacher assistive robot in a kindergarten

Sound design for emotion and intention expression of socially interactive robots

The current concept of robots has been greatly influenced by the image of robots from science fiction. Since robots were introduced into human society as partners with them, the importance of human–robot interaction has grown. In this paper, we have designed seven musical sounds, five of which express intention and two that express emotion for the English teacher robot, Silbot. To identify the sound design considerations, we analyzed the sounds of robots, R2-D2 and Wall-E, from two popular movies, Star Wars and Wall-E, respectively. From the analysis, we found that intonation, pitch, and timbre are dominant musical parameters to express intention and emotion. To check the validity of these designed sounds for intention and emotion, we performed a recognition rate experiment. The experiment showed that the five designed sounds for intentions and the two for emotions are sufficient to deliver the intended emotions.

Computational Model of Emotion Generation for Human–Robot Interaction Based on the Cognitive Appraisal Theory

Interactions between humans and service robots are more natural when emotions can be synthesized in those robots. Cognitive appraisal theory of emotions provides a theoretical basis for designing artificial emotion generation systems for robots. Computational algorithms to implement the cognitive appraisal theory were proposed in this research. The algorithms were based on a probabilistic description about the world. The proposed model was applied to a sample of interactive tasks, and the robot's emotions during the task execution can lead to a more positive human---robot interaction experience.