Designing a robot to evaluate group formations

Robots are making their way in environments inhabited by people. Whether in domestic or public crowded environments, robots should take into consideration social norms and behaviors in order to become a social robot. This dissertation focuses on the problem of how to develop a robotic platform in order to validate human-robot interaction experiences in realistic environments. More specifically, we are concerned with social interactions in human-robot groups in public scenarios, where a variety of people can converge. Our final goal is the develop of a social robot based on certain theories of group behavior and the use of space, known as spatial relationships. The intermediate goals are related with the design and development of the experiences in the wild: as minor changes as possible in the scenario, definition of social tasks, gradual development of a robotic platform as transparent as possible from the robotic side. Initially, this research introduces several preliminary studies of human-robot interaction (HRI) with the PAL Robotics’ REEM robot at the CosmoCaixa Science Museum in Barcelona. Based on certain theories about the use of space as a form of social communication or interaction, the task under study with the commercial robot is as a museum guide, both when the group was in motion (\ie when it was being guided) as well as a group in a static place. Moreover, a second HRI study with REEM robot accomplishing the task of a teacher's assistant was carried out to analyze the perception of the robot's social presence and identity. Likewise, the development of a robotic platform, known as MASHI, for the study of HRI is presented. Based on the service to be completed by the robot, improvements in the experimental robotic platform (structure, morphology, head, face, arms) were carried out in continuous cycles following the development of HRI experiences. This structure should be hold as simple as possible in order to make it `transparent' in the social HRI study. Next, the field study of human-robot social interaction with the MASHI robot with the role of exhibition guide in a cultural center is presented. Based on direct observation techniques, a study is made of the different spatial relationships that are generated when a robot interacts with a person or groups of people. Finally, a novel approach to represent the spatial relationships of HRI in a qualitative way is introduced for future experiences. In this concluding study, we analyze different spatial arrangements generated in a social scenario with a robot within the guide role. As a main conclusion, it can be stated that people follow social norms, in the form of spatial relationships, when interacting with a robot that provide a social service in a public space. Children, however, recurrently challenge these social norms, probably because they are constantly learning about the norms that regulate our coexistence. Spatial relationships are clearly reinforced when the role assigned to the robot is more explicit and understood by people. Spatial relationships can be affected by the characteristics of the environment, either by the available space or by the elements arranged in it, as well as by the number of people who inhabit it. Overall, this dissertation points out that the provided service, and its understanding from the user’s side, is more important that the robotic skills of the robotic platform in order to improve user experiences in public environments.Los robots se abren paso en entornos habitados por personas. Ya sea en entornos domésticos o públicos, los robots deben tener en cuenta ciertas normas y comportamientos sociales para convertirse en un robot social. Esta disertación se centra en el problema de cómo desarrollar una plataforma robótica para validar experiencias de interacción humano-robot en entornos realistas. Más específicamente, nos preocupamos por las interacciones sociales en grupos humano-robot en escenarios públicos, donde una gran variedad de personas puede converger. Nuestro objetivo final es el desarrollo de un robot social basado en ciertas teorías de comportamiento grupal y el uso del espacio, conocidas como relaciones espaciales. Los objetivos intermedios están relacionados con el diseño y desarrollo de las experiencias `en la naturaleza': cambios mínimos como sea posible en el escenario, definición de tareas sociales, desarrollo gradual de una plataforma robótica lo más transparente posible desde el lado robótico. Inicialmente, esta investigación presenta varios estudios preliminares de interacción humano-robot (HRI) con el robot REEM de PAL Robotics en el Museo de Ciencias CosmoCaixa de Barcelona. Basado en ciertas teorías sobre el uso del espacio como una forma de comunicación o interacción social, la tarea en este estudio con el robot comercial es como guía de museo, tanto cuando el grupo estaba en movimiento (es decir, cuando estaba siendo guiado) como cuando el grupo estaba en un lugar estático. Además, se llevó a cabo un segundo estudio de HRI con un robot REEM que realizaba la tarea de un asistente de profesor para analizar la percepción de la presencia e identidad social del robot. Asimismo, se presenta el desarrollo de una plataforma robótica, conocida como MASHI, para el estudio de la HRI. En función del servicio que debe completar el robot, las mejoras en la plataforma robótica experimental (estructura, morfología, cabeza, cara, brazos) se llevaron a cabo en ciclos continuos siguiendo el desarrollo de las experiencias de HRI. Esta estructura debe mantenerse lo más simple posible para que sea 'transparente' en el estudio de HRI social. A continuación, se presenta el estudio de campo de la interacción social humano-robot con el robot MASHI con el papel de guía de exposición en un centro cultural. Con base en técnicas de observación directa, se realiza un estudio de las diferentes relaciones espaciales que se generan cuando un robot interactúa con una persona o grupos de personas. Finalmente, se introduce un enfoque novedoso para representar las relaciones espaciales de la HRI de forma cualitativa para las experiencias futuras. En este estudio final, analizamos diferentes arreglos espaciales generados en un escenario social con un robot con el rol de guía. Como conclusión principal, se puede afirmar que las personas siguen normas sociales, en forma de relaciones espaciales, cuando interactúan con un robot que brinda un servicio social en un espacio público. Los niños, sin embargo, desafían recurrentemente estas normas sociales, probablemente porque están aprendiendo constantemente sobre las normas que regulan nuestra convivencia. Las relaciones espaciales se refuerzan claramente cuando el rol asignado al robot es más explícito y entendido por las personas. Las relaciones espaciales pueden verse afectadas por las características del entorno, ya sea por el espacio disponible o por los elementos dispuestos en él, así como por el número de personas que lo habitan. En general, esta disertación señala que el servicio prestado, y su comprensión del lado del usuario, es más importante que las habilidades robóticas de la plataforma robótica con el fin de mejorar las experiencias del usuario en entornos público

Designing a robot to evaluate group formations

Robots are making their way in environments inhabited by people. Whether in domestic or public crowded environments, robots should take into consideration social norms and behaviors in order to become a social robot. This dissertation focuses on the problem of how to develop a robotic platform in order to validate human-robot interaction experiences in realistic environments. More specifically, we are concerned with social interactions in human-robot groups in public scenarios, where a variety of people can converge. Our final goal is the develop of a social robot based on certain theories of group behavior and the use of space, known as spatial relationships. The intermediate goals are related with the design and development of the experiences in the wild: as minor changes as possible in the scenario, definition of social tasks, gradual development of a robotic platform as transparent as possible from the robotic side. Initially, this research introduces several preliminary studies of human-robot interaction (HRI) with the PAL Robotics’ REEM robot at the CosmoCaixa Science Museum in Barcelona. Based on certain theories about the use of space as a form of social communication or interaction, the task under study with the commercial robot is as a museum guide, both when the group was in motion (\ie when it was being guided) as well as a group in a static place. Moreover, a second HRI study with REEM robot accomplishing the task of a teacher's assistant was carried out to analyze the perception of the robot's social presence and identity. Likewise, the development of a robotic platform, known as MASHI, for the study of HRI is presented. Based on the service to be completed by the robot, improvements in the experimental robotic platform (structure, morphology, head, face, arms) were carried out in continuous cycles following the development of HRI experiences. This structure should be hold as simple as possible in order to make it `transparent' in the social HRI study. Next, the field study of human-robot social interaction with the MASHI robot with the role of exhibition guide in a cultural center is presented. Based on direct observation techniques, a study is made of the different spatial relationships that are generated when a robot interacts with a person or groups of people. Finally, a novel approach to represent the spatial relationships of HRI in a qualitative way is introduced for future experiences. In this concluding study, we analyze different spatial arrangements generated in a social scenario with a robot within the guide role. As a main conclusion, it can be stated that people follow social norms, in the form of spatial relationships, when interacting with a robot that provide a social service in a public space. Children, however, recurrently challenge these social norms, probably because they are constantly learning about the norms that regulate our coexistence. Spatial relationships are clearly reinforced when the role assigned to the robot is more explicit and understood by people. Spatial relationships can be affected by the characteristics of the environment, either by the available space or by the elements arranged in it, as well as by the number of people who inhabit it. Overall, this dissertation points out that the provided service, and its understanding from the user’s side, is more important that the robotic skills of the robotic platform in order to improve user experiences in public environments.Los robots se abren paso en entornos habitados por personas. Ya sea en entornos domésticos o públicos, los robots deben tener en cuenta ciertas normas y comportamientos sociales para convertirse en un robot social. Esta disertación se centra en el problema de cómo desarrollar una plataforma robótica para validar experiencias de interacción humano-robot en entornos realistas. Más específicamente, nos preocupamos por las interacciones sociales en grupos humano-robot en escenarios públicos, donde una gran variedad de personas puede converger. Nuestro objetivo final es el desarrollo de un robot social basado en ciertas teorías de comportamiento grupal y el uso del espacio, conocidas como relaciones espaciales. Los objetivos intermedios están relacionados con el diseño y desarrollo de las experiencias `en la naturaleza': cambios mínimos como sea posible en el escenario, definición de tareas sociales, desarrollo gradual de una plataforma robótica lo más transparente posible desde el lado robótico. Inicialmente, esta investigación presenta varios estudios preliminares de interacción humano-robot (HRI) con el robot REEM de PAL Robotics en el Museo de Ciencias CosmoCaixa de Barcelona. Basado en ciertas teorías sobre el uso del espacio como una forma de comunicación o interacción social, la tarea en este estudio con el robot comercial es como guía de museo, tanto cuando el grupo estaba en movimiento (es decir, cuando estaba siendo guiado) como cuando el grupo estaba en un lugar estático. Además, se llevó a cabo un segundo estudio de HRI con un robot REEM que realizaba la tarea de un asistente de profesor para analizar la percepción de la presencia e identidad social del robot. Asimismo, se presenta el desarrollo de una plataforma robótica, conocida como MASHI, para el estudio de la HRI. En función del servicio que debe completar el robot, las mejoras en la plataforma robótica experimental (estructura, morfología, cabeza, cara, brazos) se llevaron a cabo en ciclos continuos siguiendo el desarrollo de las experiencias de HRI. Esta estructura debe mantenerse lo más simple posible para que sea 'transparente' en el estudio de HRI social. A continuación, se presenta el estudio de campo de la interacción social humano-robot con el robot MASHI con el papel de guía de exposición en un centro cultural. Con base en técnicas de observación directa, se realiza un estudio de las diferentes relaciones espaciales que se generan cuando un robot interactúa con una persona o grupos de personas. Finalmente, se introduce un enfoque novedoso para representar las relaciones espaciales de la HRI de forma cualitativa para las experiencias futuras. En este estudio final, analizamos diferentes arreglos espaciales generados en un escenario social con un robot con el rol de guía. Como conclusión principal, se puede afirmar que las personas siguen normas sociales, en forma de relaciones espaciales, cuando interactúan con un robot que brinda un servicio social en un espacio público. Los niños, sin embargo, desafían recurrentemente estas normas sociales, probablemente porque están aprendiendo constantemente sobre las normas que regulan nuestra convivencia. Las relaciones espaciales se refuerzan claramente cuando el rol asignado al robot es más explícito y entendido por las personas. Las relaciones espaciales pueden verse afectadas por las características del entorno, ya sea por el espacio disponible o por los elementos dispuestos en él, así como por el número de personas que lo habitan. En general, esta disertación señala que el servicio prestado, y su comprensión del lado del usuario, es más importante que las habilidades robóticas de la plataforma robótica con el fin de mejorar las experiencias del usuario en entornos públicosPostprint (published version

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

Influencing robot learning through design and social interactions: a framework for balancing designer effort with active and explicit interactions

This thesis examines a balance between designer effort required in biasing a robot’s learn-ing of a task, and the effort required from an experienced agent in influencing the learning using social interactions, and the effect of this balance on learning performance. In order to characterise this balance, a two dimensional design space is identified, where the dimensions represent the effort from the designer, who abstracts the robot’s raw sensorimotor data accord-ing to the salient parts of the task to increasing degrees, and the effort from the experienced agent, who interacts with the learner robot using increasing degrees of complexities to actively accentuate the salient parts of the task and explicitly communicate about them. While the in-fluence from the designer must be imposed at design time, the influence from the experienced agent can be tailored during the social interactions because this agent is situated in the environ-ment while the robot is learning. The design space is proposed as a general characterisation of robotic systems that learn from social interactions. The usefulness of the design space is shown firstly by organising the related work into the space, secondly by providing empirical investigations of the effect of the various influences o

Biologically inspired computational structures and processes for autonomous agents and robots

Recent years have seen a proliferation of intelligent agent applications: from robots for space exploration to software agents for information filtering and electronic commerce on the Internet. Although the scope of these agent applications have blossomed tremendously since the advent of compact, affordable computing (and the recent emergence of the World Wide Web), the design of such agents for specific applications remains a daunting engineering problem;Rather than approach the design of artificial agents from a purely engineering standpoint, this dissertation views animals as biological agents, and considers artificial analogs of biological structures and processes in the design of effective agent behaviors. In particular, it explores behaviors generated by artificial neural structures appropriately shaped by the processes of evolution and spatial learning;The first part of this dissertation deals with the evolution of artificial neural controllers for a box-pushing robot task. We show that evolution discovers high fitness structures using little domain-specific knowledge, even in feedback-impoverished environments. Through a careful analysis of the evolved designs we also show how evolution exploits the environmental constraints and properties to produce designs of superior adaptive value. By modifying the task constraints in controlled ways, we also show the ability of evolution to quickly adapt to these changes and exploit them to obtain significant performance gains. We also use evolution to design the sensory systems of the box-pushing robots, particularly the number, placement, and ranges of their sensors. We find that evolution automatically discards unnecessary sensors retaining only the ones that appear to significantly affect the performance of the robot. This optimization of design across multiple dimensions (performance, number of sensors, size of neural controller, etc.) is implicitly achieved by the evolutionary algorithm without any external pressure (e.g., penalty on the use of more sensors or neurocontroller units). When used in the design of robots with limited battery capacities , evolution produces energy-efficient robot designs that use minimal numbers of components and yet perform reasonably well. The performance as well as the complexity of robot designs increase when the robots have access to a spatial learning mechanism that allows them to learn, remember, and navigate to power sources in the environment;The second part of this dissertation develops a computational characterization of the hippocampal formation which is known to play a significant role in animal spatial learning. The model is based on neuroscientific and behavioral data, and learns place maps based on interactions of sensory and dead-reckoning information streams. Using an estimation mechanism known as Kalman filtering, the model explicitly deals with uncertainties in the two information streams, allowing the robot to effectively learn and localize even in the presence sensing and motion errors. Additionally, the model has mechanisms to handle perceptual aliasing problems (where multiple places in the environment appear sensorily identical), incrementally learn and integrate local place maps, and learn and remember multiple goal locations in the environment. We show a number of properties of this spatial learning model including computational replication of several behavioral experiments performed with rodents. Not only does this model make significant contributions to robot localization, but also offers a number of predictions and suggestions that can be validated (or refuted) through systematic neurobiological and behavioral experiments with animals

Proceedings of the NASA Conference on Space Telerobotics, volume 5

Papers presented at the NASA Conference on Space Telerobotics are compiled. The theme of the conference was man-machine collaboration in space. The conference provided a forum for researchers and engineers to exchange ideas on the research and development required for the application of telerobotics technology to the space systems planned for the 1990's and beyond. Volume 5 contains papers related to the following subject areas: robot arm modeling and control, special topics in telerobotics, telerobotic space operations, manipulator control, flight experiment concepts, manipulator coordination, issues in artificial intelligence systems, and research activities at the Johnson Space Center