This article aims to give an approach of a dynamic and emotional
propagation, which allows to calculate the propagation of the emotion
of a group of humans and/or intelligent entities. The dynamic model
is based on the Newton laws in order to calculate the emotional attraction
among them. To obtain the emotions we use a NAO robot as a tool
to move around of a real environment for interacting with the humans.
The robot obtains the emotions through image processing. Moreover, the
robot can start a dialogue game with humans in order to estimate the
personality of a new individual.This work is partially supported by the MINECO project TIN2015-65515-C4-1-
R and the FPI grant AP2013-01276 awarded to Jaime-Andres Rincon

Carrascosa, C.

Costa, Ângelo Gonçalo Araújo Silva

Julian, V.

Novais, Paulo

Rincon, J. A.

Universidade do Minho: RepositoriUM

Detecting Social Emotions with a NAO robotJ. A. Rincon1, A. Costa2, P. Novais2, V. Julian1, C. Carrascosa11 Universitat Polite`cnica de Vale`ncia. D. Sistemas Informa´ticos y Computacio´n{jrincon, vinglada, carrasco@dsic.upv.es}2 Centro ALGORITMI, Escola de Engenharia, Universidade do Minho, Guimara˜es{acosta, pjon@di.uminho.pt}Abstract. This article aims to give an approach of a dynamic and emo-tional propagation, which allows to calculate the propagation of the emo-tion of a group of humans and/or intelligent entities. The dynamic modelis based on the Newton laws in order to calculate the emotional attrac-tion among them. To obtain the emotions we use a NAO robot as a toolto move around of a real environment for interacting with the humans.The robot obtains the emotions through image processing. Moreover, therobot can start a dialogue game with humans in order to estimate thepersonality of a new individual.1 IntroductionHuman beings manage themselves in different environments, either in the work-ing place, at home or in public places. In each of these places the human interactswith other human beings. In this interaction the humans can express and/orperceive the emotion of the other humans that have around them. In this per-ception is possible that a human could be influenced by the emotion expressedfor other human. In such a scenario if you could distinguish two elements thatcould influence the emotional contagion, the first is the level of affinity that haveboth individuals and the second is how empathetic is the agent that perceivesthe emotion. This two situations have been taken into account in our dynamicemotional model. The empathy has a correlation with the personality [1], theempathy is related with Agreeableness. The empathy level can be extracted us-ing the OCEAN test estimating the personality of the human beings. This testallows to know which is the personality of the human and to use these valuesto get a personality estimation. Intelligent agents technology have emerged asa way for the development of autonomous entities in order to act on behalf ofpeople anticipating their decision-making processes. Therefore, these artificialintelligent entities may include the capabilities and required elements that willhelp them to recognize and simulate emotions[2].2 Dynamic Emotional ModelThis section proposes a dynamic emotional model based on the PAD emotionalmodel. This model will represent the emotional contagion of an heterogeneousgroup of entities capable of expressing and/or communicating emotions. Theemotional representation of an emotional state of an agent on the PAD model,the emotion of an agent agi in an instant t (#»Et(agi)) is defined as a vector inR3. The variation of each component allows to modify the emotional state of theagent (Equation 1).#»Et(agi) = [Pt(agi), At(agi), Dt(agi)] (1)The emotional dynamics described is based on the Newton universal attrac-tion law. Based on this theory, we define the force that an agent agj makesover an agent agi at instant t (#»F t(agi, agj)) to attract or repulse it in the PADspace, that is, this force will control the emotion contagion between all the agents.(Equation 2).#»F t(agi, agj) =ε(agi) · Aft(agi, agj)2Dt(agi,agj)· || #»Et(agi)− #»Et(agj)|| (2)#»F t(agi, agj) represents the force vector, which contains all the mathematicalproperties of vectors as, direction and magnitude. Using these elements help usto know if the emotion of the agent agi is attracted by the agent agj . ε(agi) rep-resents the emphatic level of entity agi, and Aft(agi, agj) represents the affinitylevel between agi and agj at instant t. Dt(agi, agj) is the physical distance be-tween agi and agj at instant t and#»Et(agi) represents the emotion of the agi atinstant t and#»Et(agj) represents the emotion of the agj at instant t. Accordingwith this, we define the Emotional Attraction Forces of agent agi at instant t,as as summation of all forces over agent agi at instant t. Using this forces andfollowing the Newton laws we calculate the velocity ans finally using this velocitywe calculate the new emotion. This new emotion is a PAD vector for entity agiat instant t + 1 (#»Et+1(agj)) (Equation 3).#»Et+1(agj) =#»Et(agj) + (#»v t(agi) · t) (3)The proposed dynamic model allows us to model and represent the emotionalcontagion phenomena among different intelligent agents. Nevertheless, these en-tities typically are not alone in the environment but are part of a group of agents.Our proposal is to model not only how an agent is influenced by other agentsbut also how the group of agents as a whole can be emotionally affected by itscomponents. To do this, we employ the social emotional model defined in [3].Due to space limitations, please refer to that work for a detailed explanation ofthe model. Using this model, it is possible to determine the emotional distanceamong different groups of agents or between the same group in different instantsof time. This will allow us to measure the emotional distance between the cur-rent social emotional group and a possible emotional target. Next subsectionshows an application where a mobile robot implements the two models allowingthe robot to estimate and represent the emotional contagion of a heterogeneousgroup of people and observe how the robot can influence over the social emotionof that group of people.3 DemoThe application example has been developed in a real environment, where thereis a NAO robot 3 in charge of interacting with humans in a room. The main goalof the proposed example is the automatic recognition of the emotional states of agroup of individuals in order to enhance the wellbeing of these individuals. To dothis, the robot is moving around the room and tries to interact with any detectedperson. The robot calculates the emotional states of the group of identified in-dividuals and, according to the proposed model, it estimates possible emotionalcontagions among individuals. In order to make this process it uses differenttools to communicate with its environment and to obtain the information thatsurrounds it:– Speech recognition, the robot speaks with people to try to change their emo-tional states. Moreover, if the robot does not know the person, it estimateshis personality using a dialogue game that follows the OCEAN test.– Robot movement, the robot is continually moving around the room tryingto interact and animate any individual presented in the room.– Image processing, used to detect the emotional state of people around theroom. To detect the emotional states, the robot employs the API presented inthe project oxford4. This project can support the detection and evaluationof around 64 faces extracting the emotion of each one of them. We usethese results in order to calculate the emotional dynamic according to thepreviously presented dynamic emotional model.Figure 1 shows a simulated environment of the proposed application wherewe can see the NAO robot interacting with a group of three individuals.Fig. 1: Simulation of the proposed applicationWith this information, the robot tries to animate and stimulate people whichis in the room. This stimulation actions are performed when the robot detects3 https://www.aldebaran.com/en4 https://www.projectoxford.ai/emotional changes that lead to social emotion to move away from a target emo-tion (happiness, usually). This continuous sensorization of the robot environ-ment, allows to estimate the emotional dynamics of the group and thus therobot is able to react performing different actions like telling a joke, asking whathappens to them or make a funny action. One of the possible applications of thissystem is in nursing homes, where they have to perform tasks playful. The robotwould be responsible for carrying out these tasks while analyzing emotions andmodifying its actions according to the emotion of the group.[4].4 Conclusions and future workA new model for the calculation of dynamic emotions has been presented inthis paper, giving a first approach for the emotional contagion and simulationof dynamic social emotions into a group of intelligent entities. The proposedmodel uses the personality of each entity and the affinity level between entitiesin order to calculate and represent the emotional dynamic of a group. The dy-namic emotional model of a group of agents not only allows a global view of theemotional dynamic of the group, also can improve the decision making based onthe attraction level between entities. The paper introduces also a demo abouthow to calculate, represent and use the dynamic emotional model into a realenvironment. The proposed application consists of a NAO mobile robot whichuses the proposed emotional model to enhance its decision-making process.5 AcknowledgementsThis work is partially supported by the MINECO project TIN2015-65515-C4-1-R and the FPI grant AP2013-01276 awarded to Jaime-Andres Rincon.References1. William G Graziano, Meara M. Habashi, Brad E. Sheese, and Rene´e M Tobin.Agreeableness, empathy, and helping: A person x situation perspective. Journal ofPersonality and Social Psychology, 93(4):583–599, 2007.2. J.A. Rincon, V. Julian, and C. Carrascosa. Applying a Social Emotional Model inHuman-Agent Societies. In Workshop WIHAS’15. Intelligent Human-Agent Soci-eties., volume 524 of CCIS, pages 377–388, 2015.3. J. A. Rincon, V. Julian, and C. Carrascosa. Social Emotional Model. In Advancesin Practical Applications of Agents, Multi-Agent Systems, and Sustainability: ThePAAMS Collection, pages 199–210. Springer, 2015.4. Ewa Niewiadomska-Szynkiewicz and Andrzej Sikora. Progress in Automation,Robotics and Measuring Techniques. Advances in Intelligent Systems and Com-puting, 351:181–190, 2015.

Detecting social emotions with a NAO robot

http://repositorium.sdum.uminho.pt/bitstream/1822/44821/1/2016%20-%20PAAMS%20-%20Detecting%20Social%20Emotions%20with%20a%20NAO%20robot.pdf

Detecting social emotions with a NAO robot

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