A challenge in Human-Robot Interaction is tailoring the social skills of robot companions to match those expected by individual humans during their rst encounter. Currently, large amounts of user data are needed to con gure robot companions with these skills. This creates the need of running long-term Human-Robot Interaction studies in domestic environments. A new approach using personas is explored to alleviate this arduous data collection task without compromising the level of interaction currently shown by robot companions. The personas technique was created by Alan Cooper in 1999 as a tool to de ne user archetypes of a system in order to reduce the involvement of real users during the development process of a target system. This technique has proven bene cial in Human-Computer Interaction for years. Therefore, similar bene ts could be expected when applying personas to Human-Robot Interaction. Our novel approach de nes personas as the key component of a computational behaviour model used to adapt robot companions to individual user's needs. This approach reduces the amount of user data that must be collected before a Human-Robot Interaction study, by associating new users to pre-de ned personas that adapt the robot behaviours through their integration with the computational behaviour model. At the same time that the current robot social interaction level expected by humans during the rst encounter is preserved. The University of Hertfordshire Robot House provided the naturalistic domestic environment for the investigation. After incorporating a new module, an Activity Recognition System, to increase the overall context-awareness of the system, a computational behaviour model will be de ned through an iterative research process. The initial de nition of the model was evolved after each experiment based on the iii ndings. Two successive studies investigated personas and determined the steps to follow for their integration into the targeted model. The nal model presented was de ned from users' preferences and needs when interacting with a robot companion during activities of daily living at home. The main challenge was identifying the variables that match users to personas in our model. This approach open a new discussion in the Human-Robot Interaction eld to de ne tools that help reduce the amount of user data requiring collection prior to the rst interaction with a robot companion in a domestic environment. We conclude that modelling people's preferences when interacting with robot companions is a challenging approach. Integrating the Human-Computer Interaction technique into a computational behaviour model for Human-Robot Interaction studies was more di cult than anticipated. This investigation shows the advantages and disadvantages of introducing this technique into Human-Robot Interaction, and explores the challenges in de ning a personas-based computational behaviour model. The continuous learning process experienced helps clarify the steps that other researchers in the eld should follow when investigating a similar approach. Some interesting outcomes and trends were also found among users' data, which encourage the belief that the personas technique can be further developed to tackle some of the current di culties highlighted in the Human-Robot Interaction literature.

De nos jours, les robots compagnons présentent de réelles capacités et fonctionnalités. Leurs acceptabilité dans nos habitats est cependant toujours un objet d'étude du fait que les motivations et la valeur du companionage entre robot est enfant n'a pas encore été établi. Classiquement, les robots sociaux avaient des comportements génériques qui ne prenaient pas en compte les différences inter-individuelles. De plus en plus de travaux en Interaction Humain-Robot se penchent sur la personnalisation du compagnon. Personnalisation et contrôle du compagnon permettrai une meilleure compréhension de ses comportements par l'utilisateur. Proposer une palette d'expressions du compagnon jouant un rôle social permettrait à l'utilisateur de customiser leur compagnon en fonction de leur préférences.Dans ce travail, nous proposons un système de plasticité pour l'interaction humain-robot. Nous utilisons une méthode de Design Basée Scenario pour expliciter les rôles sociaux attendu des robot compagnons. Puis en nous appuyant sur la littérature de plusieurs disciplines, nous proposons de représenter ces variations de comportement d'un robot compagnon par les styles comportementaux. Les styles comportementaux sont défini en fonction du rôle social grâce à des paramètres d'expressivité non-verbaux. Ces paramètres (statiques, dynamiques et décorateurs) permettent de transformer des mouvements dit neutres en mouvements stylés. Nous avons mener une étude basée sur des vidéos, qui montraient deux robots avec des mouvement stylés, afin d'évaluer l'expressivité de deux styles parentaux par deux types de robots. Les résultats montrent que les participants étaient capable de différentier les styles en termes de dominance et d'autorité, en accord avec la théorie en psychologie sur ces styles. Nous avons constater que le style préféré par les parents n'étaient pas corréler à leur propre style en tant que parents. En conséquence, les styles comportementaux semblent être des outils pertinents pour la personnalisation social du robot compagnon par les parents.Une seconde expérience, dans un appartement impliquant 16 enfants dans des interaction enfant-robot, a montré que parents et enfants attendent plutôt d'un robot d'être polyvalent et de pouvoir jouer plusieurs rôle à la maison. Cette étude a aussi montré que les styles comportementaux ont une influence sur l'attitude corporelle des enfants pendant l'interaction avec le robot. Des dimensions classiquement utilisées en communication non-verbal nous ont permises de développer des mesures pour l'interaction enfant-robot, basées sur les données capturées avec un capteur Kinect 2.Dans cette thèse nous proposons également la modularisation d'une architecture cognitive et affective précédemment proposé résultant dans l'architecture Cognitive et Affective orientées Interaction (CAIO) pour l'interaction social humain-robot. Cette architecture a été implémenter en ROS, permettant son utilisation par des robots sociaux. Nous proposons aussi l'implémentation des Stimulus Evaluation Checks (SECs) de [Scherer, 2009] pour deux plateformes robotiques permettant l'expression dynamique d'émotion.Nous pensons que les styles comportementaux et l'architecture CAIO pourront s'avérer utile pour l'amélioration de l'acceptabilité et la sociabilité des robot compagnons. / Companion robots are technologically and functionally more and more efficient. Capacities and usefulness of companion robots is nowadays a reality. These robots that have now more efficient are however not accepted yet in home environments as worth of having such robot and companionship hasn't been establish. Classically, social robots were displaying generic social behaviours and not taking into account inter-individual differences. More and more work in Human-Robot Interaction goes towards personalisation of the companion. Personalisation and control of the companion could lead to better understanding of the robot's behaviour. Proposing several ways of expression for companion robots playing role would allow user to customize their companion to their social preferences.In this work, we propose a plasticity framework for Human-Robot Interaction. We used a Scenario-Based Design method to elicit social roles for companion robots. Then, based on the literature in several disciplines, we propose to depict variations of behaviour of the companion robot with behavioural styles. Behavioural styles are defined according to the social role with non-verbal expressive parameters. The expressive parameters (static, dynamic and decorators) allow to transform neutral motions into styled motion. We conducted a perceptual study through a video-based survey showing two robots displaying styles allowing us to evaluate the expressibility of two parenting behavioural styles by two kind robots. We found that, participants were indeed able to discriminate between the styles in term of dominance and authoritativeness, which is in line with the psychological theory on these styles. Most important, we found that styles preferred by parents for their children was not correlated to their own parental practice. Consequently, behavioural styles are relevant cues for social personalisation of the companion robot by parents.A second experimental study in a natural environment involving child-robot interaction with 16 children showed that parents and children were expected a versatile robot able to play several social role. This study also showed that behavioural styles had an influence on the child's bodily attitudes during the interaction. Common dimension studied in non-verbal communication allowed us to develop measures for child-robot interaction, based on data captured with a Kinect2 sensor .In this thesis, we also propose a modularisation of a previously proposed affective and cognitive architecture resulting in the new Cognitive, Affective Interaction Oriented (CAIO) architecture. This architecture has been implemented in ROS framework allowing it to use it on social robots. We also proposed instantiations of the Stimulus Evaluation Checks of [Scherer, 2009]for two robotic platforms allowing dynamic expression of emotions.Both behavioural style framework and CAIO architecture can be useful in socialise companion robots and improving their acceptability.

Dans ce travail, nous considérons le cas d'un robot mobile d'intérieur dont l'objectif est de détecter les humains présents dans l'environnement et de se positionner physiquement par rapport à eux, dans le but de mieux percevoir leur état. Pour cela, le robot dispose de différents capteurs (capteur RGB-Depth, microphones, télémètre laser). Des contributions de natures variées ont été effectuées :Classification d'événements sonores en environnement intérieur : La méthode de classification proposée repose sur une taxonomie de petite taille et est destinée à différencier les marqueurs de la présence humaine. L'utilisation de fonctions de croyance permet de prendre en compte l'incertitude de la classification, et de labelliser un son comme « inconnu ».Fusion audiovisuelle pour la détection de locuteurs successifs dans une conversation : Une méthode de détection de locuteurs est proposée dans le cas du robot immobile, placé comme témoin d'une interaction sociale. Elle repose sur une fusion audiovisuelle probabiliste. Cette méthode a été testée sur des vidéos acquises par le robot.Navigation dédiée à la détection d'humains à l'aide d'une fusion multimodale : A partir d'informations provenant des capteurs hétérogènes, le robot cherche des humains de manière autonome dans un environnement connu. Les informations sont fusionnées au sein d'une grille de perception multimodale. Cette grille permet au robot de prendre une décision quant à son prochain déplacement, à l'aide d'un automate reposant sur des niveaux de priorité des informations perçues. Ce système a été implémenté et testé sur un robot Q.bo.Modélisation crédibiliste de l'environnement pour la navigation : La construction de la grille de perception multimodale est améliorée à l'aide d'un mécanisme de fusion reposant sur la théorie des fonctions de croyance. Ceci permet au robot de maintenir une grille « évidentielle » dans le temps comprenant l'information perçue et son incertitude. Ce système a d'abord été évalué en simulation, puis sur le robot Q.bo. / In this work, we consider the case of mobile robot that aims at detecting and positioning itself with respect to humans in its environment. In order to fulfill this mission, the robot is equipped with various sensors (RGB-Depth, microphones, laser telemeter). This thesis contains contributions of various natures:Sound classification in indoor environments: A small taxonomy is proposed in a classification method destined to enable a robot to detect human presence. Uncertainty of classification is taken into account through the use of belief functions, allowing us to label a sound as "unknown".Speaker tracking thanks to audiovisual data fusion: The robot is witness to a social interaction and tracks the successive speakers with probabilistic audiovisual data fusion. The proposed method was tested on videos extracted from the robot's sensors.Navigation dedicated to human detection thanks to a multimodal fusion:} The robot autonomously navigates in a known environment to detect humans thanks to heterogeneous sensors. The data is fused to create a multimodal perception grid. This grid enables the robot to chose its destinations, depending on the priority of perceived information. This system was implemented and tested on a Q.bo robot.Credibilist modelization of the environment for navigation: The creation of the multimodal perception grid is improved by the use of credibilist fusion. This enables the robot to maintain an evidential grid in time, containing the perceived information and its uncertainty. This system was implemented in simulation first, and then on a Q.bo robot.

Robot assisted therapy is becoming increasingly popular. Research has proven it can be of benefit to persons dealing with a variety of disorders, such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and it can also provide a source of emotional support e.g. to persons living in seniors’ residences. The advancement in technology and a decrease in cost of products related to consumer electronics, computing and communication has enabled the development of more advanced social robots at a lower cost. This brings us closer to developing such tools at a price that makes them affordable to lower income individuals and families. Currently, in several cases, intensive treatment for patients with certain disorders (to the level of becoming effective) is practically not possible through the public health system due to resource limitations and a large existing backlog. Pursuing treatment through the private sector is expensive and unattainable for those with a lower income, placing them at a disadvantage. Design and effective integration of technology, such as using social robots in treatment, reduces the cost considerably, potentially making it financially accessible to lower income individuals and families in need. The Objective of the research reported in this manuscript is to design and implement a social robot that meets the low-cost criteria, while also containing the required functions to support children with ASD. The design considered contains knowledge acquired in the past through research involving the use of various types of technology for the treatment of mental and/or emotional disabilities.