Notice bibliographique
Résumé
Robots are rapidly advancing toward becoming autonomous and skilled entities in a wide range of environments, and it is likely that more and more people will soon be interacting with robots in their everyday lives. As this happens, we believe that it is crucial that robots are designed to be easy to use and understand, reducing the requirement for people and environments to adapt to the robot. Emerging research in Human-Robot Interaction (HRI) suggests that people have a strong natural tendency to treat robots as social entities, anthropomorphizing, zoomorphizing, and generally attributing them with social characteristics and roles. Our approach to HRI is to explicitly focus on the social layers of interaction, building robotic interfaces that use people’s existing skill sets, and that explicitly attempt to integrate into familiar social structures. We refer to this approach of directly considering HRI in the context of the social human world as social HRI. The field of social HRI is only just emerging: there is little general discussion which explains why social HRI is important or what exactly social HRI means, there is no methodology for approaching the specific consideration of designing and implementing social HRI interfaces, and there is no structured methodology for evaluating and studying social HRI. There are few social HRI interface designs and implementations—those that focus on social interaction between people and robots—and the scope of social HRI interaction possibilities is still relatively unexplored. In this dissertation we present what we believe is the first thorough exploration of the theory, design, implementation, and evaluation of social HRI. We present a detailed analysis of social HRI, drawing particularly from selected works in social psychology and philosophy, and compose a social HRI-targeted theory that addresses why people tend toward social interaction with robots, how robots can leverage this, and what the implications are for both users and designers. We present a set of social HRI interfaces we designed, implemented and evaluated as a means to demonstrate and reflect on the practical and technical feasibility of applying social HRI principles to robot interface designs. We present the results from several extensive user studies, which we conducted as a means to learn from our interfaces, and to test, reflect on and further develop our social HRI theories. Finally, we distill our overall efforts into a set of some of the very first social HRI-specific design heuristics. Overall, our work highlights the importance of considering the broad landscape of social interaction between people and robots, and the usefulness of explicitly considering social aspects for robotic interaction design. We hope that by establishing the foundational social HRI groundwork, this dissertation will lead to and support continuing development of social HRI theory and new social HRI interface designs as this emerging domain evolves and grows.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».