Human-robot social interaction plays an important role in spreading the use of the robot in human daily life. Through effective social interaction, robots will be able to perform many tasks in the human society. These tasks may include, but not limited to, handling various house duties, providing medical care for elderly people, assisting people with motor or cognitive disabilities, educational entertainment (edutainment), personal assistance, giving directions at information points in public places, etc. These applications need to develop social robots that are able to behave with humans as partners if not peers. This paper presents Maggie, a robotic platform developed at RoboticsLab for research on human-robot social interaction. The different developed interaction modules are also described.

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One of the main challenges faced by social robots is how to provide intuitive, natural and enjoyable usability for the end-user. In our ordinary environment, social robots could be important tools for education and entertainment (edutainment) in a variety of ways. This paper presents a Natural Programming System (NPS) that is geared to non-expert users. The main goal of such a system is to provide an enjoyable interactive platform for the users to build different programs within their social robot platform. The end-user can build a complex net of actions and conditions (a sequence) in a social robot via mixed-initiative dialogs and multimodal interaction. The system has been implemented and tested in Maggie, a real social robot with multiple skills, conceived as a general HRI researching platform. The robot's internal features (skills) have been implemented to be verbally accessible to the end-user, who can combine them into others more complex following a bottom-up model. The built sequence is internally implemented as a Sequence Function Chart (SFC), which allows parallel execution, modularity and re-use. A multimodal Dialog Manager System (DMS) takes charge of keeping the coherence of the interaction. This work is thought for bringing social robots closer to non-expert users, who can play the game of "teaching how to do things" with the robot.

Resumen: En este artículo se presenta, en forma de tutorial, una visión de conjunto de la situación actual del problema de la toma de decisiones en robótica. El estudio se plantea de forma amplia e integradora y, por tanto, intentando no entrar en detallar soluciones concretas para problemas también concretos. El artículo está centrado sobre todo en las decisiones de alto nivel que debe tomar un robot, y no en problemas de más bajo nivel, que se solucionan empleando técnicas tradicionales de control o mediante algoritmos muy específicos. Nos referimos a "toma de decisiones" de un robot en el sentido amplio de determinar las actividades a realizar por el robot. Es decir, sin hacer ninguna exclusión a priori, basada en cuestiones tales como la estrategia de toma de decisiones empleada, el tipo de robot, las tareas que puede realizar, etc. El artículo está estructurado en una serie de secciones, en las que se tratan diversos temas de interés en robótica, desde la perspectiva de la toma de decisiones: autonomía, inteligencia, objetivos, decisiones de alto nivel, estrategias de toma de decisiones, arquitecturas de control, percepción, interacción humano-robot, aprendizaje y emociones.