In robotic rehabilitation therapies, knowledge of human joint torques is important for patient safety, to provide a reliable data for clinical assessment and to increase control performance of the device, nevertheless, its measurement can be complex or have a highcost implementation. The most of techniques for torque estimation have been developed for upper limb robotic rehabilitation devices, in addition, they typically require detailed anthropometric and musculoskeletal models. In this dissertation is presented the ankle torque estimation for the Anklebot robot, the estimation uses an ankle/Anklebot dynamic model that consider the ankle joint angular displacement and velocity measurement, its mechanical impedance parameters are obtained through a second-order modeled mechanical impedance of the ankle and an identification of frictional and gravitational torques. Three approaches for the ankle torque estimation were proposed to be implemented in the Anklebot robot, the Generalized Momentum, the Kalman filter and finally a combination of both the above mentioned approaches. The validation of such approaches was developed first on a physical mockup configured to reproduce the human ankle joint movement, by assessing its performances, the Kalman filter approach was selected to be implemented on a voluntary subject. A set of experiments were performed considering the physical activity that the subject may realize when interacting with the Anklebot, the developed ankle torque estimation proved to be successful for passive torque and in most of the proposed scenarios where active torque is performed. / Em terapias de reabilitação robótica, o conhecimento dos torques da articulação humana é importante para a segurança do paciente, para fornecer dados confiáveis na avaliação clínica e aumentar o desempenho de controle do dispositivo, no entanto, sua medição pode ser complexa ou costoso de implementar. A maioria das técnicas de estimativa de torque tem sido desenvolvidas para dispositivos de reabilitação robótica de membros superiores, além disso, eles normalmente requerem modelos antropométricos e musculoesqueléticos detalhados. Nesta dissertação é apresentada a estimativa do torque do tornozelo no robô Anklebot, a estimação utiliza um modelo dinâmico tornozelo + Anklebot o qual considera a medição da posição e velocidade angular do tornozelo, os parametros de impedancia mecânica do tornozelo são obtidos por meio de um modelo simples de segunda ordem e são identificados os torques gravitacionais e de atrito. Três abordagens para a estimativa de torque de tornozelo foram propostas para serem implementadas, o momento generalizado, o filtro de Kalman e, finalmente, uma abordagem que combina tanto o momento generalizado e o filtro de Kalman. A validação de tais abordagens foi desenvolvida primeiro em um mock-up físico configurado para reproduzir o movimento articular do tornozelo humano, avaliando seus desempenhos. A segunda abordagem proposta foi selecionada para ser implementada em um usuário voluntário. Um conjunto de experimentos foi realizado considerando a atividade física que o sujeito pode realizar ao interagir com o Anklebot, a estimativa desenvolvida de torque de tornozelo demostrou ser bem sucedida para o torque passivo e na maioria dos cenários propostos onde o torque ativo é realizado.

Development in robotics has been accelerated in the last decades. Mainly due to the advancement in technology, especially computers. However, even having enough technology to create robots that can participate in the daily lives of people, robotics has not become popular, once that the most robots purchased by people still fall into the category of toys, monitoring systems, among others. The search for such robots is due to the fact that their repertoire of tasks is so much limited and predetermined, which ultimately facilitate the interaction between users and robots. Meanwhile, more sophisticated robots, in most cases, can only be used by specialized people, because they have a larger task repertoire, which needs more complex interaction mechanisms. In others areas, such as computing, the communication interface was of fundamental importance for its popularization. This way, the construction of friendly communication interfaces between people and robots can be the key to robotics can be widespread in the actual society. However, not every interface can provide an easy and e cient communication. An e ective interface should be as intuitive as possible, what, according the psycholinguistics studies, can be achieved through the use of spontaneous gestures. Therefore, knowing the di cult to nd a procedure to obtain intuitive gesture vocabularies, this master thesis proposes a methodology that, based on psycholinguistics and HCI (Human-Computer Interaction) studies, is suitable to obtain intuitive gesture vocabularies to be used in HRI (Human-Robot Interaction). Therefore, after the application of this methodology, it was possible to notice that it was able to lead to results as good as those obtained by another methodology which is already used and accepted in HCI. Moreover, the proposed methodology has some distinct characteristics, such as the possibility to obtain more complex vocabularies, that can lead to more intuitive gesture vocabularies and which, in form, are more likely to be robust. In addition, by submitting the obtained gestures to a recognizer, an average hit rate of 77,5% was obtained, which, even though it is not so high, can be considered good enough, since some of the gestures are performed with both arms, increasing the complexity of the recognition task. Thus, at the end of this master thesis, some complementary works are proposed, which must be carried out in order to move further towards the development of intuitive interfaces for human-robot interaction. / O desenvolvimento da rob otica vem ganhando acelera c~ao desde as ultimas d ecadas, motivado principalmente pelo avan co da tecnologia, sobretudo dos computadores. No entanto, mesmo tendo tecnologia su ciente para criar rob^os que possam participar do cotidiano das pessoas, a rob otica ainda n~ao se popularizou, haja vista que a maioria dos rob^os adquiridos pelas pessoas ainda se enquadram na categoria de brinquedos, sistemas de monitoramento, dentre outros. A busca por esses tipos de rob^os se deve ao fato de que seu repert orio de tarefas e bem reduzido e predeterminado, o que acaba facilitando a intera c~ao entre usu arios e rob^os. Enquanto isso, rob^os mais so sticados, por possu rem um maior repert orio de tarefas, acabam necessitando de mecanismos de intera c~ao mais complexos que, em sua maioria, s o podem ser utilizados por pessoas especializadas. Em outras areas, como a inform atica, a interface de comunica c~ao foi de fundamental import^ancia para a sua populariza c~ao. Dessa maneira, a cria c~ao de interfaces amig aveis de comunica c~ao entre pessoas e rob^os pode ser a chave para que a rob otica tamb em possa ser amplamente difundida na sociedade atual. No entanto, n~ao e qualquer interface que pode oferecer uma comunica c~ao f acil e e ciente. Para isso as mesmas devem ser o mais intuitivas poss vel, o que, segundo os estudos psicolingu sticos, pode ser alcan cado por meio de gestos espont^aneos. Logo, sabendo da di culdade de se encontrar um procedimento que ofere ca a possibilidade de se obter vocabul arios de gestos intuitivos, esta disserta c~ao de mestrado prop~oe uma metodologia que, baseada na psicolingu stica e nos estudos sobre HCI (do ingl^es - Human Computer Interaction), ofere ce facilidade no processo de obten c~ao de vocabul arios de gestos intuitivos a serem utilizados na intera c~ao entre pessoas e rob^os. Desta maneira, ap os a aplica c~ao de tal metodologia, p^ode-se perceber que a mesma, apesar de ser nova, al em de poder levar a resultados t~ao bons quanto uma outra metodologia j a utilizada e aceita em HCI, ainda possui diferenciais, como a possibilidade de obter vocabul arios mais complexos, que podem levar a vocabul arios de gestos mais intuitivos e possivelmente mais robustos. Al em disso, ao submeter os gestos obtidos a um reconhecedor, obteve-se uma taxa m edia de acertos de 77,5%, que mesmo n~ao sendo alta, pode ser considerada boa, pois, uma vez que alguns gestos obtidos s~ao realizados com os dois bra cos, a complexidade do reconhecimento e aumentada de maneria consider avel. Assim, ao nal desta disserta c~ao, s~ao apresentados v arios trabalhos complementares a este, que devem ser realizados para que se possa avan car ainda mais na dire c~ao do desenvolvimento das interfaces intuitivas para a intera c~ao homem-rob^o.

A robótica social representa um ramo da interação humano-robô que visa desenvolver robôs para atuar em ambientes não estruturados em parceria direta com seres humanos. O relatório A Roadmap for U.S. Robotics From Internet to Robotics, de 2013, preconiza a obtenção de resultados promissores em 12 anos desde que condições apropriadas sejam disponibilizadas para a área. Uma das condições envolve a utilização de ambiente de referência para desenvolver, avaliar e comparar o desempenho de sistemas cognitivos. Este ambiente é denominado Robot City com atores, cenários (casas, ruas, cidade) e auditores. Até o momento esse complexo ambiente não se concretizou, possivelmente devido ao elevado custo de implantação e manutenção de uma instalação desse porte. Nesta dissertação é proposto um caminho alternativo através da definição e implementação do simulador de sistemas cognitivos denominado Robot House Simulator (RHS). O simulador RHS tem como objetivo disponibilizar um ambiente residencial composto por sala e cozinha, no qual convivem dois agentes, um robô humanoide e um avatar humano. O agente humano é controlado pelo usuário do sistema e o robô é controlado por uma arquitetura cognitiva que determina o comportamento do robô. A arquitetura cognitiva estabelece sua percepção do ambiente através de informações sensoriais supridas pelo RHS e modeladas por uma ontologia denominada OntSense. A utilização de uma ontologia garante rigidez formal aos dados sensoriais além de viabilizar um alto nivel de abstração. O RHS tem como base a ferramenta de desenvolvimento de jogos Unity sendo aderente ao conceito de código aberto com disponibilização pelo repositório online GitHub. A validação do sistema foi realizada através de experimentos que demonstraram a capacidade do simulador em prover um ambiente de validação para arquiteturas cognitivas voltadas à robótica social. O RHS é pioneiro na integração de um simulador e uma arquitetura cognitiva, além disto, é um dos poucos direcionados para robótica social provendo rica informação sensorial, destacando-se o modelamento inédito disponibilizado para os sentidos de olfato e paladar. / Social robotics represents a branch of human-robot interaction that aims to develop robots to work in unstructured environments in direct partnership with humans. The Roadmap for Robotics from the Internet to Robotics, 2013, predicts achieving promising results in 12 years as long as appropriate conditions are made available to the area. One of the conditions involves the use of a reference environment to develop, evaluate and compare the performance of cognitive systems. This environment is called Robot City with actors, scenarios (houses, streets, city) and auditors. To date, this complex environment has not been materialized, possibly due to its high cost of installing and maintaining. In this dissertation an alternative way is proposed through the definition and implementation of the simulator of cognitive systems called Robot House Simulator (RHS). The RHS simulator aims to provide a residential environment composed of living room and kitchen, in which two agents live together, a humanoid robot and a human avatar. The human avatar is controlled by the user of the system and the robot is controlled by a cognitive architecture that determines the behavior of the robot. The cognitive architecture establishes its perception of the environment through sensorial information supplied by the RHS and modeled by an ontology called OntSense. The use of an ontology guarantees formal rigidity to the sensory data in addition to enabling a high level of abstraction. The RHS simulator is based on the Unity game engine and is adheres to the open source concept, available on the GitHub online repository. The validation of the system was performed through experiments that demonstrated the simulators ability to provide a validation environment for cognitive architectures aimed at social robotics. The RHS simulator is a pioneer in the integration of a simulator and a cognitive architecture. In addition, it is one of the few for social robotics to provide rich sensory information where it is worth noting the unprecedented modeling available to the senses of smell and taste.

Hier fiction, maintenant réalité, le robot humanoïde, machine intelligente créée sur le modèle humain, concrétise des rêves ancestraux, avec pour ambition que la copie puisse égaler ou dépasser son modèle et créateur ; voire effectuer un bond dans l’évolution, par delà l’altérité homme/machine et la finitude. Afin de questionner ce qui sous-tend la réalisation du robot, ses enjeux, et ce que ses caractéristiques disent de l’homme aujourd’hui, cette réflexion revisite ses traces mythologiques et techniques depuis l’Antiquité, puis aborde les principaux axes de recherche en robotique interactive. Au regard de la contextualité contemporaine sous le règne de la science et du néolibéralisme, et marquée par l’imaginaire de la science-fiction, des nouvelles technologies, et par l’héritage de la mort collective du 20e siècle ; sont examinésles fantasmes originaires et la dynamique pulsionnelle (concernant notamment l’emprise et la satisfaction, les interactions précoces, et la formation du double) à l’oeuvre dans l’avènement du robot humanoïde. En approchant ce que l’humain reproduit sciemment dans son double technologique, et tout ce qu’à son insu il y dépose, transparaît l’empreinte de la répétition et des tentatives de subjectivation de la place du sujet dans la filiation et du legs transgénérationnel en ce qu’il a d’irreprésentable ou de traumatique. Tenant de l’invention scientifique, du symptôme, de l’objet transitionnel et de l’oeuvre d’art, le robot humanoïde procède d’une double résistance, se traduisant en potentialités de répétition aliénante ou de subjectivation réparatrice, susceptibles de s’actualiser pendant la réalisation du robot ou dans l’interaction avec lui. / Yesterday a fiction, now a reality, the humanoid robot, an intelligent machine designed after the human model, embodies ancestral dreams, with the aim that the copy meets or exceeds its model and creator, or even makes a jump in evolution, beyond the difference between humans and machines and beyond death. This study addresses what underlies the realization of robots, the challenges they open up to, and what their characteristics may say about humans today.After examining the mythological and technical origins of the robot, it presents today’s key research topics in the field of human-robot interaction. With regards to the contemporary context dominated by science and neoliberalism, and marked by the imagination of science fiction and new technologies, as well as by the 20th century’s collective death inheritance,this work studies the original fantasies and the drive dynamics involved in the advent of the humanoid robot. The repetition compulsion and the human attempts to subjectify their position in the lineage and their transgenerational legacy in its unrepresentable or traumatic parts, show when approaching what humans deliberately reproduce in their artificial double,as well as what they deposit in it unknowingly. Though mainly a scientific invention and a technological tool, the humanoid robot may be regarded as a symptom, a transitional object or a piece of art. This particular status translates into a double ambivalent psychological resistance: constructing the humanoid robot and interacting with it, may develop into analienating repetition compulsion, as well as revive the subjectivation process.

Que cela soit par des automates puis par des robots, l'Homme a été fasciné par des machines pouvant exécuter des tâches pour lui, dans de nombreux domaines, comme l'industrie ou les services : c'est ce dernier domaine qui nous sert de contexte. Ainsi, nous avons utilisé une approche développementale, où le robot se doit d'apprendre de nouvelles tâches au cours de sa vie. Inspiré par des théories sur le développement de l'enfant, nous avons extrait les concepts intéressants pour les implémenter sur une plateforme robotique humanoïde : l'iCub. L'acquisition du langage est une première étape, où la capacité à classifier les mots, de classes ouvertes et de classes fermées permet d'obtenir une syntaxe qui aide l'enfant à construire le lien entre une phrase et son sens. Cette méthode a été implémentée grâce à un réseau de neurones récurrents, utilisant une base de données fournit par l'humain en interagissant avec le robot. La maîtrise du langage permet à l'enfant de participer à des actions plus complexes, en particulier des tâches collaboratives où la parole est requise de négocier le mode d'apprentissage sur plusieurs modalités. Implémenté sur l'iCub et le Nao, cela permet un apprentissage en temps réel et de réaliser un plan partagé. Enfin, nous avons étudié le fonctionnement de la mémoire autobiographique, cruciale pour se remémorer des épisodes passés de sa vie, d'en tirer des prédictions et de les appliquer dans le futur. En recréant cette mémoire en SQL et formatant les données en PDDL, l'iCub est alors capable de raisonner en fonction de sa propre expérience, lui permettant ainsi de résoudre le problème des Tours d'Hanoi sans jamais l'avoir visualisé avant / From automata to robots, the Human has always been fascinated by machines which could execute tasks for him, in several domains like industry or services. Indeed, we have used a developmental approach, where the robot has to learn new tasks during his life. Inspired by theories in child development, we have extracted the interesting concepts to implement them on a humanoid robotic platform : the iCub. Language acquisition is a first step, where the capacity to classify closed and opened class words allows to obtain a syntax which help the children to make the link between a sentence and its meaning. This method has been implemented with a recurrent neural network, using a database provided from the human by interaction with the robot. The control of the language allows the children to participate in more complex actions, in particular cooperative tasks, where speech is required to negotiate the learning mode within several modalities. Implemented on the iCub and the Nao, this allows a real-time learning and to realize a shared plan. Eventually, we have studied the functioning of the autobiographical memory, crucial toremember episodes of his life, to extract predictions from and to apply them in the future. By recreating this memory in SQL, and by formatting the data in PDDL, the iCub is then capable of reasoning in function of his own experience, allowing him to solve the Tower of Hanoi problem without knowing the solution before

Detta arbete har utförts inom ramarna för SIDUS-projektet AIR och fokuserar på interaktion mellan människa och autonoma och sociala robotar. Inom fältet för människa- robotinteraktion (MRI) ökar medvetenheten kring hur viktigt en positiv användarupplevelse (eng. user experience, UX) av dessa interaktioner är. När intresset för UX blir större ökar också behovet av att kunna arbeta med det på ett korrekt och lämpligt sätt. Idag finns det ett stort behov av metoder och tekniker för UX-arbete som är anpassade efter detta komplexa gränssnitt. Det övergripande syftet med detta arbete är därför att minska detta behov genom både en teoretisk litteraturstudie samt ett empiriskt arbete. I litteraturstudien kunde endast två ramverk ämnade för UX-utvärdering av MRI identifieras, varav ett av dem, USUS-ramverket, anses erbjuda en god grund för arbete med UX-utvärdering inom MRI. Fokus för det empiriska arbetet har sedan varit att förbättra och modifiera detta ramverk genom att integrera UX-mål som en del av det. UX-mål pekas ut som en central del för all sorts UX-arbete och är något som också kan optimera de utvärderingar som sker. Därför bör det också vara en del av det UX-arbete som sker inom MRI-fältet. Detta presenteras sedan i en ny version av USUS-ramverket, kallat USUS Goals. Baserat på dessa teoretiska och empiriska studier presenteras sedan riktlinjer för hur det fortsatta arbetet med UX- utvärdering inom MRI bör ske. Slutresultatet visar bland annat att utmaningarna med att integrera UX som del av MRI-fältet är större än vad som först antagits. Utmaningen ligger inte endast i att skapa användbara och anpassade UX-metoder, det är snarare ett ömsesidigt ansvar för båda domänerna att mötas för att tillsammans adressera dessa utmaningar. / Action and Intention Recognition in human interaction with autonomous systems (AIR)

Que ce soit dans un contexte industriel ou quotidien, les robots deviennent de plus en plus présents dans notre environnement et sont désormais capables d'interagir avec des humains. Dans les milieux industriels, des robots viennent notamment assister les opérateurs des chaînes d'assemblage pour des tâches fatigantes et dangereuses. Robots et opérateurs sont alors amenés à partager le même espace physique (coprésence) et à effectuer des tâches en commun (collaboration). Alors que la sécurité des humains à proximité des robots doit être garantie à tout instant, il convient également de déterminer si le travail collaboratif est accepté par les opérateurs, en termes d'utilisabilité et d'utilité.La première problématique de la thèse consiste à déterminer quelles sont les composantes importantes rentrant en jeu dans l'acceptabilité de la collaboration homme-robot, du point de vue des opérateurs. Différents facteurs peuvent influencer cette acceptabilité : l'apparence des robots et leurs mouvements, la distance de sécurité ou encore le mode d'interaction avec le robot.Afin d'étudier le maximum de facteurs, nous proposons d'utiliser la réalité virtuelle pour mener des tests utilisateurs en environnement virtuel. Nous utilisons des questionnaires pour recueillir les impressions subjectives des opérateurs et des mesures physiologiques pour estimer leur état affectif (stress, effort). La deuxième problématique de la thèse consiste à déterminer si une méthodologie utilisant la réalité virtuelle est pertinente pour cette évaluation : les résultats issus des tests en environnement virtuel rendent-ils bien compte de la situation réelle ?Pour répondre aux problématiques de la thèse, trois cas d'étude ont été mis en place et quatre expérimentations ont été menées. Deux de ces expérimentations ont été reproduites à la fois en environnements réel et virtuel afin d'évaluer la pertinence des résultats issus de la situation virtuelle par rapport à la situation réelle. / Either in the context of the industry or of the everyday life, robots are becoming more and more present in our environment and are nowadays able to interact with humans. In industrial environments, robots now assist operators on the assembly lines for difficult and dangerous tasks. Then, robots and operators need to share the same physical space (copresence) and to manage common tasks (collaboration). On the one side, the safety of humans working near robots has to be guaranteed at all time. On the other hand, it is necessary to determine if such a collaborative work is accepted by the operators, in terms of usability and utility.The first problematic of the thesis consists in determining the important criteria that play a role in the acceptability, from the operators' point of view. Different factors can influence this acceptability: robot appearance, robot movements, safety distance or interaction modes with the robot.In order to study as many factors as possible, we intend to use virtual reality to perform user studies in virtual environments. We are using questionnaires to gather subjective impressions from operators and physiological measures to estimate their affective states (stress, effort). The second problematic of the thesis consists in determining if a methodology using virtual reality is relevant for this evaluation: can the results from studies in virtual environments be reproducible in equivalent physical situations?In order to answer the problematics of the thesis, three use cases have been implemented and four studies have been performed. Two of those studies rely on a physical situation and its virtual reality counterpart in order to evaluate the relevance of the results of the virtual situation compared to the real situation.

Les robots collaboratifs sont de plus en plus présents dans nos vies quotidiennes. En milieu industriel, ils sont une solution privilégiée pour rendre les chaînes de montage plus flexibles, rentables et diminuer la pénibilité du travail des opérateurs. Pour permettre une collaboration fluide et efficace, les robots doivent être capables de comprendre leur environnement, en particulier les actions humaines.Dans cette optique, nous avons décidé d’étudier la reconnaissance de gestes techniques afin que le robot puisse se synchroniser avec l’opérateur, adapter son allure et comprendre si quelque chose d’inattendu survient.Pour cela, nous avons considéré deux cas d’étude, un cas de co-présence et un cas de collaboration, tous les deux inspirés de cas existant sur les chaînes de montage automobiles.Dans un premier temps, pour le cas de co-présence, nous avons étudié la faisabilité de la reconnaissance des gestes en utilisant des capteurs inertiels. Nos très bons résultats (96% de reconnaissances correctes de gestes isolés avec un opérateur) nous ont encouragés à poursuivre dans cette voie.Sur le cas de collaboration, nous avons privilégié l’utilisation de capteurs non-intrusifs pour minimiser la gêne des opérateurs, en l’occurrence une caméra de profondeur positionnée avec une vue de dessus pour limiter les possibles occultations.Nous proposons un algorithme de suivi des mains en calculant les distances géodésiques entre les points du haut du corps et le haut de la tête. Nous concevons également et évaluons un système de reconnaissance de gestes basé sur des Chaînes de Markov Cachées (HMM) discrètes et prenant en entrée les positions des mains. Nous présentons de plus une méthode pour adapter notre système de reconnaissance à un nouvel opérateur et nous utilisons des capteurs inertiels sur les outils pour affiner nos résultats. Nous obtenons le très bon résultat de 90% de reconnaissances correctes en temps réel pour 13 opérateurs.Finalement, nous formalisons et détaillons une méthodologie complète pour réaliser une reconnaissance de gestes techniques sur les chaînes de montage. / Collaborative robots are becoming more and more present in our everyday life. In particular, within the industrial environment, they emerge as one of the preferred solution to make assembly line in factories more flexible, cost-effective and to reduce the hardship of the operators’ work. However, to enable a smooth and efficient collaboration, robots should be able to understand their environment and in particular the actions of the humans around them.With this aim in mind, we decided to study technical gestures recognition. Specifically, we want the robot to be able to synchronize, adapt its speed and understand if something unexpected arises.We considered two use-cases, one dealing with copresence, the other with collaboration. They are both inspired by existing task on automotive assembly lines.First, for the co-presence use case, we evaluated the feasibility of technical gestures recognition using inertial sensors. We obtained a very good result (96% of correct recognition with one operator) which encouraged us to follow this idea.On the collaborative use-case, we decided to focus on non-intrusive sensors to minimize the disturbance for the operators and we chose to use a depth-camera. We filmed the operators with a top view to prevent most of the potential occultations.We introduce an algorithm that tracks the operator’s hands by calculating the geodesic distances between the points of the upper body and the top of the head.We also design and evaluate an approach based on discrete Hidden Markov Models (HMM) taking the hand positions as an input to recognize technical gestures. We propose a method to adapt our system to new operators and we embedded inertial sensors on tools to refine our results. We obtain the very good result of 90% of correct recognition in real time for 13 operators.Finally, we formalize and detail a complete methodology to realize technical gestures recognition on assembly lines.

Au cours des dernières années, la communauté robotique s'est largement intéressée au domaine de l'interaction homme-robot (HRI). Un des aspects de ce domaine est de faire agir les robots en présence de l'homme, tout en respectant sa sécurité ainsi que son confort. Pour atteindre cet objectif, un robot doit planifier ses actions tout en prenant explicitement en compte les humains afin d'adapter le plan à leurs positions, leurs capacités et leurs préférences. La première partie de cette thèse concerne les transferts d'objets entre humains et robots : où, quand et comment les effectuer? Dépendant des préférences de l'Homme, il est parfois préférable, ou pas, partager l'effort du transfert d'objet entre lui et le robot, mais encore, à certains moments, un seul transfert d'objet n'est pas suffisant pour atteindre l'objectif (amener l'objet à un agent cible), le robot doit alors planifier une séquence de transfert d'objet entre plusieurs agents afin d'arriver à ses fins. Quel que soit le cas, pendant le transfert d'objet, un certain nombre de signaux doivent être échangés par les deux protagonistes afin de réussir l'action. Un des signaux les plus utilisés est le regard. Lorsque le donneur tend le bras afin de transférer l'objet, il doit regarder successivement le receveur puis l'objet afin de faciliter le transfert. Le transfert d'objet peut être considéré comme une action de base dans un plan plus vaste, nous amenant à la seconde partie de cette thèse qui présente une formalization de ce type d'actions de base" et d'actions plus complexes utilisant des conditions, des espaces de recherche et des contraintes. Cette partie rend aussi compte du framework et des différents algorithmes utilisés pour résoudre et calculer ces actions en fonction de leur description. La dernière partie de la thèse montre comment ce framework peut s'adapter à un planificateur de plus haut niveau (un planificateur de tâches par exemple) et une méthode pour combiner la planification symbolique et géométrique. Le planificateur de tâches utilise des appels à des fonctions externes lui permettant de vérifier la faisabilité de la tâche courante, et en cas de succès, de récupérer l'état du monde fourni par le raisonneur géométrique et de l'utilisé afin de poursuivre la planification. Cette partie montre également différentes extensions de cette algorithme, tels que les \validation géométriques" où nous testons l'infaisabilité de plusieurs actions à la fois ou \les contraintes" où l'ajout de contraintes au niveau symbolique peut dirigée la recherche géométrique ou encore \recherche dirigé par coût" où le planificateur symbolique utilise les informations fournies par la partie géométrique afin d'éviter le calcul de plans moins intéressants. / In the last few years, the Human robot interaction (HRI) field has been in the spotlight of the robotics community. One aspect of this field is making robots act in the presence of humans, while keeping them safe and comfortable. In order to achieve this, a robot needs to plan its actions while explicitly taking into account the humans and adapt its plans to their whereabouts, capacities and preferences. The first part of this thesis is about human-robot handover: where, when and how to perform them? Depending on the human preferences, it may be better, or not, to share the handover effort between him and the robot, while in other cases, a unique handover might not be enough to achieve the goal (bringing the object to a target agent) and a sequence of handovers might be needed. In any case, during the handover, a number of cues should be used by both protagonists involved in one handover. One of the most used cue is the gaze. When the giver reaches out with his arm, he should look at the object, and when the motion is finished, he should look at the receiver's face to facilitate the transfer. The handover can be considered as a basic action in a bigger plan. The second part of this thesis reports about a formalization of these kind of basic actions" and more complex ones by the use of conditions, search spaces and restraints. It also reports about a framework and different algorithms used to solve and compute these actions based on their description. The last part of the thesis shows how the previously cited framework can fit in with a higher level planner (such as a task planner) and a method to combine a symbolic and geometric planner. The task planner uses external calls to the geometric planner to assess the feasibility of the current task, and in case of success, retrieve the state of the world provided by the geometric reasoner and use it to continue the planning. This part also shows different extensions enabling a faster search. Some of these extensions are \Geometric checks" where we test the infeasibility of multiple actions at once, \constraints" where adding constraints at the symbolic level can drive the geometric search, and \cost driven search" where the symbolic planner uses information form the geometric one to prune out over costly plans.

With the great advancement in robot technology, smart human-robot interaction is considered to be the most wanted success by the researchers these days. If a robot can identify emotions and intentions of a human interacting with it, that would make robots more useful. Electroencephalography (EEG) is considered one effective way of recording emotions and motivations of a human using brain. Various machine learning techniques are used successfully to classify EEG data accurately. K-Nearest Neighbor, Bayesian Network, Artificial Neural Networks and Support Vector Machine are among the suitable machine learning techniques to classify EEG data. The aim of this thesis is to evaluate different machine learning techniques to classify EEG data associated with specific affective/emotional states. Different methods based on different signal processing techniques are studied to find a suitable method to process the EEG data. Various number of EEG data features are used to identify those which give best results for different classification techniques. Different methods are designed to format the dataset for EEG data. Formatted datasets are then evaluated on various machine learning techniques to find out which technique can accurately classify EEG data according to associated affective/emotional states. Research method includes conducting an experiment. The aim of the experiment was to find the various emotional states in subjects as they look on different pictures and record the EEG data. The obtained EEG data is processed, formatted and evaluated on various machine learning techniques to find out which technique can accurately classify EEG data according to associated affective/emotional states. The experiment confirms the choice of a technique for improving the accuracy of results. According to the results, Support Vector Machine is the first and Regression Tree is the second best to classify EEG data associated with specific affective/emotional states with accuracies up to 70.00% and 60.00% respectively. SVM is better in performance than RT. However, RT is famous for providing better accuracies for diverse EEG data.