The effects of user assistance systems on user perception and behavior

The rapid development of information technology (IT) is changing how people approach and interact with IT systems (Maedche et al. 2016). IT systems can increasingly support people in performing ever more complex tasks (Vtyurina and Fourney 2018). However, people's cognitive abilities have not evolved as quickly as technology (Maedche et al. 2016). Thus, different external factors (e.g., complexity or uncertainty) and internal conditions (e.g., cognitive load or stress) reduce decision quality (Acciarini et al. 2021; Caputo 2013; Hilbert 2012). User-assistance systems (UASs) can help to compensate for human weaknesses and cope with new challenges. UASs aim to improve the user's cognition and capabilities, benefiting individuals, organizations, and society. To achieve this goal, UASs collect, prepare, aggregate, analyze information, and communicate results according to user preferences (Maedche et al. 2019). This support can relieve users and improve the quality of decision-making. Using UASs offers many benefits but requires successful interaction between the user and the UAS. However, this interaction introduces social and technical challenges, such as loss of control or reduced explainability, which can affect user trust and willingness to use the UAS (Maedche et al. 2019). To realize the benefits, UASs must be developed based on an understanding and incorporation of users' needs. Users and UASs are part of a socio-technical system to complete a specific task (Maedche et al. 2019). To create a benefit from the interaction, it is necessary to understand the interaction within the socio-technical system, i.e., the interaction between the user, UAS, and task, and to align the different components. For this reason, this dissertation aims to extend the existing knowledge on UAS design by better understanding the effects and mechanisms during the interaction between UASs and users in different application contexts. Therefore, theory and findings from different disciplines are combined and new theoretical knowledge is derived. In addition, data is collected and analyzed to validate the new theoretical knowledge empirically. The findings can be used to reduce adaptation barriers and realize a positive outcome. Overall this dissertation addresses the four classes of UASs presented by Maedche et al. (2016): basic UASs, interactive UASs, intelligent UASs, and anticipating UASs. First, this dissertation contributes to understanding how users interact with basic UASs. Basic UASs do not process contextual information and interact little with the user (Maedche et al. 2016). This behavior makes basic UASs suitable for application contexts, such as social media, where little interaction is desired. Social media is primarily used for entertainment and focuses on content consumption (Moravec et al. 2018). As a result, social media has become an essential source of news but also a target for fake news, with negative consequences for individuals and society (Clarke et al. 2021; Laato et al. 2020). Thus, this thesis presents two approaches to how basic UASs can be used to reduce the negative influence of fake news. Firstly, basic UASs can provide interventions by warning users of questionable content and providing verified information but the order in which the intervention elements are displayed influences the fake news perception. The intervention elements should be displayed after the fake news story to achieve an efficient intervention. Secondly, basic UASs can provide social norms to motivate users to report fake news and thereby stop the spread of fake news. However, social norms should be used carefully, as they can backfire and reduce the willingness to report fake news. Second, this dissertation contributes to understanding how users interact with interactive UASs. Interactive UASs incorporate limited information from the application context but focus on close interaction with the user to achieve a specific goal or behavior (Maedche et al. 2016). Typical goals include more physical activity, a healthier diet, and less tobacco and alcohol consumption to prevent disease and premature death (World Health Organization 2020). To increase goal achievement, previous researchers often utilize digital human representations (DHRs) such as avatars and embodied agents to form a socio-technical relationship between the user and the interactive UAS (Kim and Sundar 2012a; Pfeuffer et al. 2019). However, understanding how the design features of an interactive UAS affect the interaction with the user is crucial, as each design feature has a distinct impact on the user's perception. Based on existing knowledge, this thesis highlights the most widely used design features and analyzes their effects on behavior. The findings reveal important implications for future interactive UAS design. Third, this dissertation contributes to understanding how users interact with intelligent UASs. Intelligent UASs prioritize processing user and contextual information to adapt to the user's needs rather than focusing on an intensive interaction with the user (Maedche et al. 2016). Thus, intelligent UASs with emotional intelligence can provide people with task-oriented and emotional support, making them ideal for situations where interpersonal relationships are neglected, such as crowd working. Crowd workers frequently work independently without any significant interactions with other people (Jäger et al. 2019). In crowd work environments, traditional leader-employee relationships are usually not established, which can have a negative impact on employee motivation and performance (Cavazotte et al. 2012). Thus, this thesis examines the impact of an intelligent UAS with leadership and emotional capabilities on employee performance and enjoyment. The leadership capabilities of the intelligent UAS lead to an increase in enjoyment but a decrease in performance. The emotional capabilities of the intelligent UAS reduce the stimulating effect of leadership characteristics. Fourth, this dissertation contributes to understanding how users interact with anticipating UASs. Anticipating UASs are intelligent and interactive, providing users with task-related and emotional stimuli (Maedche et al. 2016). They also have advanced communication interfaces and can adapt to current situations and predict future events (Knote et al. 2018). Because of these advanced capabilities anticipating UASs enable collaborative work settings and often use anthropomorphic design cues to make the interaction more intuitive and comfortable (André et al. 2019). However, these anthropomorphic design cues can also raise expectations too high, leading to disappointment and rejection if they are not met (Bartneck et al. 2009; Mori 1970). To create a successful collaborative relationship between anticipating UASs and users, it is important to understand the impact of anthropomorphic design cues on the interaction and decision-making processes. This dissertation presents a theoretical model that explains the interaction between anthropomorphic anticipating UASs and users and an experimental procedure for empirical evaluation. The experiment design lays the groundwork for empirically testing the theoretical model in future research. To sum up, this dissertation contributes to information systems knowledge by improving understanding of the interaction between UASs and users in different application contexts. It develops new theoretical knowledge based on previous research and empirically evaluates user behavior to explain and predict it. In addition, this dissertation generates new knowledge by prototypically developing UASs and provides new insights for different classes of UASs. These insights can be used by researchers and practitioners to design more user-centric UASs and realize their potential benefits

Development of Human-Computer Interaction for Holographic AIs

Virtual humans and embodied conversational agents play diverse roles in real life, including game characters, chatbots, and teachers. In Augmented Reality (AR), such agents are capable of interacting with the real world. To distinguish between both types of virtual agents, AR agents were conceptually redefined as "holographic Artificial Intelligences (AIs)". Holographic AIs are embodied virtual agents interacting with real objects in Augmented Reality (AR), and can respond to events both in virtual and real environments. This thesis provides a comprehensive investigation into holographic AIs, spanning from their design to their user experience. The purpose of this thesis is to investigate the creation and use of holographic AIs, by creating specific holographic AIs, and then examining how users perceive such entities in order to contribute to the improvement of the user experience. As a result, this thesis explores the design space for and methods for creating holographic AIs, proposing the novel PICS model which include the dimensions of persona, intelligence, conviviality, and senses. Following the PICS model, a set of holographic AIs are designed by using a method of semi-automatic reconstruction. An AI that resembles a human being in appearance and behaviour is endowed with multimodal interactions capable of creating the illusion of physicality. The initial proposed model is then refined based on the experience of creation. Basic body language gestures, such as nodding and opening the arms, are insufficient to engage users, particularly when it comes to intelligent tutoring systems. Therefore, this thesis specifically focuses on an open problem, the generation of re-usable standard instructional gestures. In an experiment, key instructional movements that can be employed by holographic AIs were identified and extracted as animations. The hitherto known range of representational gestures is, epistemologically, further expanded by transformational and imitation gestures, which show how humans manipulate spatio-motor information and characterise posture using hand motion. Therefore, the model can be extended to describe the holographic AI’s behaviour. Moreover, in order to assess the empirical validity of holographic AIs, this research explores learners' trustworthiness towards this novel technology - as a key criterion for efficacy of this AI approach. Trust and trustworthiness, in terms of holographic AIs, refers to a mindset that aids users in achieving objectives based on good intentions. Young learners’ perception of trust is largely influenced by affective aspects of trust, determined by how emotionally responsive a holographic AI is. These findings contribute to the design of personal holographic AIs that can perform a series of meaningful gestures that engage the learner’s attention for learning, which in turn fosters a reliable and trustworthy relationship. Both experiments are able to extend elements by adding gestures and holistic perception to this model

Autonomous interactive intermediaries : social intelligence for mobile communication agents

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2005.Includes bibliographical references (p. 151-167).Today's cellphones are passive communication portals. They are neither aware of our conversational settings, nor of the relationship between caller and callee, and often interrupt us at inappropriate times. This thesis is about adding elements of human style social intelligence to our mobile communication devices in order to make them more socially acceptable to both user and local others. I suggest the concept of an Autonomous Interactive Intermediary that assumes the role of an actively mediating party between caller, callee, and co-located people. In order to behave in a socially appropriate way, the Intermediary interrupts with non-verbal cues and attempts to harvest 'residual social intelligence' from the calling party, the called person, the people close by, and its current location. For example, the Intermediary obtains the user's conversational status from a decentralized network of autonomous body-worn sensor nodes. These nodes detect conversational groupings in real time, and provide the Intermediary with the user's conversation size and talk-to-listen ratio. The Intermediary can 'poll' all participants of a face-to-face conversation about the appropriateness of a possible interruption by slightly vibrating their wirelessly actuated finger rings.(cont.) Although the alerted people do not know if it is their own cellphone that is about to interrupt, each of them can veto the interruption anonymously by touching his/her ring. If no one vetoes, the Intermediary may interrupt. A user study showed significantly more vetoes during a collaborative group-focused setting than during a less group oriented setting. The Intermediary is implemented as a both a conversational agent and an animatronic device. The animatronics is a small wireless robotic stuffed animal in the form of a squirrel, bunny, or parrot. The purpose of the embodiment is to employ intuitive non-verbal cues such as gaze and gestures to attract attention, instead of ringing or vibration. Evidence suggests that such subtle yet public alerting by animatronics evokes significantly different reactions than ordinary telephones and are seen as less invasive by others present when we receive phone calls. The Intermediary is also a dual conversational agent that can whisper and listen to the user, and converse with a caller, mediating between them in real time.(cont.) The Intermediary modifies its conversational script depending on caller identity, caller and user choices, and the conversational status of the user. It interrupts and communicates with the user when it is socially appropriate, and may break down a synchronous phone call into chunks of voice instant messages.by Stefan Johannes Walter Marti.Ph.D

10081 Abstracts Collection -- Cognitive Robotics

From 21.02. to 26.02.2010, the Dagstuhl Seminar 10081 ``Cognitive Robotics \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Conversational Agents in Education – A Systematic Literature Review

Conversational Agents (CAs) are widely spread in a variety of domains, such as health and customer service. There is a recent trend of increasing publications and implementations of CAs in education. We conduct a systematic literature review to identify common methodologies, pedagogical CA roles, addressed target groups, the technologies and theories behind, as well as human-like design aspects. The initially found 3329 records were systematically reduced to 252 fully coded articles. Based on the analysis of the codings, we derive further research streams. Our results reveal a research gap for long-term studies on the use of CAs in education, and there is insufficient holistic design knowledge for pedagogical CAs. Moreover, target groups other than academic students are rarely considered. We condense our findings in a morphological box and conclude that pedagogical CAs have not yet reached their full potential of long-term practical application in education

Real-time generation and adaptation of social companion robot behaviors

Social robots will be part of our future homes. They will assist us in everyday tasks, entertain us, and provide helpful advice. However, the technology still faces challenges that must be overcome to equip the machine with social competencies and make it a socially intelligent and accepted housemate. An essential skill of every social robot is verbal and non-verbal communication. In contrast to voice assistants, smartphones, and smart home technology, which are already part of many people's lives today, social robots have an embodiment that raises expectations towards the machine. Their anthropomorphic or zoomorphic appearance suggests they can communicate naturally with speech, gestures, or facial expressions and understand corresponding human behaviors. In addition, robots also need to consider individual users' preferences: everybody is shaped by their culture, social norms, and life experiences, resulting in different expectations towards communication with a robot. However, robots do not have human intuition - they must be equipped with the corresponding algorithmic solutions to these problems. This thesis investigates the use of reinforcement learning to adapt the robot's verbal and non-verbal communication to the user's needs and preferences. Such non-functional adaptation of the robot's behaviors primarily aims to improve the user experience and the robot's perceived social intelligence. The literature has not yet provided a holistic view of the overall challenge: real-time adaptation requires control over the robot's multimodal behavior generation, an understanding of human feedback, and an algorithmic basis for machine learning. Thus, this thesis develops a conceptual framework for designing real-time non-functional social robot behavior adaptation with reinforcement learning. It provides a higher-level view from the system designer's perspective and guidance from the start to the end. It illustrates the process of modeling, simulating, and evaluating such adaptation processes. Specifically, it guides the integration of human feedback and social signals to equip the machine with social awareness. The conceptual framework is put into practice for several use cases, resulting in technical proofs of concept and research prototypes. They are evaluated in the lab and in in-situ studies. These approaches address typical activities in domestic environments, focussing on the robot's expression of personality, persona, politeness, and humor. Within this scope, the robot adapts its spoken utterances, prosody, and animations based on human explicit or implicit feedback.Soziale Roboter werden Teil unseres zukünftigen Zuhauses sein. Sie werden uns bei alltäglichen Aufgaben unterstützen, uns unterhalten und uns mit hilfreichen Ratschlägen versorgen. Noch gibt es allerdings technische Herausforderungen, die zunächst überwunden werden müssen, um die Maschine mit sozialen Kompetenzen auszustatten und zu einem sozial intelligenten und akzeptierten Mitbewohner zu machen. Eine wesentliche Fähigkeit eines jeden sozialen Roboters ist die verbale und nonverbale Kommunikation. Im Gegensatz zu Sprachassistenten, Smartphones und Smart-Home-Technologien, die bereits heute Teil des Lebens vieler Menschen sind, haben soziale Roboter eine Verkörperung, die Erwartungen an die Maschine weckt. Ihr anthropomorphes oder zoomorphes Aussehen legt nahe, dass sie in der Lage sind, auf natürliche Weise mit Sprache, Gestik oder Mimik zu kommunizieren, aber auch entsprechende menschliche Kommunikation zu verstehen. Darüber hinaus müssen Roboter auch die individuellen Vorlieben der Benutzer berücksichtigen. So ist jeder Mensch von seiner Kultur, sozialen Normen und eigenen Lebenserfahrungen geprägt, was zu unterschiedlichen Erwartungen an die Kommunikation mit einem Roboter führt. Roboter haben jedoch keine menschliche Intuition - sie müssen mit entsprechenden Algorithmen für diese Probleme ausgestattet werden. In dieser Arbeit wird der Einsatz von bestärkendem Lernen untersucht, um die verbale und nonverbale Kommunikation des Roboters an die Bedürfnisse und Vorlieben des Benutzers anzupassen. Eine solche nicht-funktionale Anpassung des Roboterverhaltens zielt in erster Linie darauf ab, das Benutzererlebnis und die wahrgenommene soziale Intelligenz des Roboters zu verbessern. Die Literatur bietet bisher keine ganzheitliche Sicht auf diese Herausforderung: Echtzeitanpassung erfordert die Kontrolle über die multimodale Verhaltenserzeugung des Roboters, ein Verständnis des menschlichen Feedbacks und eine algorithmische Basis für maschinelles Lernen. Daher wird in dieser Arbeit ein konzeptioneller Rahmen für die Gestaltung von nicht-funktionaler Anpassung der Kommunikation sozialer Roboter mit bestärkendem Lernen entwickelt. Er bietet eine übergeordnete Sichtweise aus der Perspektive des Systemdesigners und eine Anleitung vom Anfang bis zum Ende. Er veranschaulicht den Prozess der Modellierung, Simulation und Evaluierung solcher Anpassungsprozesse. Insbesondere wird auf die Integration von menschlichem Feedback und sozialen Signalen eingegangen, um die Maschine mit sozialem Bewusstsein auszustatten. Der konzeptionelle Rahmen wird für mehrere Anwendungsfälle in die Praxis umgesetzt, was zu technischen Konzeptnachweisen und Forschungsprototypen führt, die in Labor- und In-situ-Studien evaluiert werden. Diese Ansätze befassen sich mit typischen Aktivitäten in häuslichen Umgebungen, wobei der Schwerpunkt auf dem Ausdruck der Persönlichkeit, dem Persona, der Höflichkeit und dem Humor des Roboters liegt. In diesem Rahmen passt der Roboter seine Sprache, Prosodie, und Animationen auf Basis expliziten oder impliziten menschlichen Feedbacks an

Bringing Human Robot Interaction towards _Trust and Social Engineering

Robots started their journey in books and movies; nowadays, they are becoming an important part of our daily lives: from industrial robots, passing through entertainment robots, and reaching social robotics in fields like healthcare or education. An important aspect of social robotics is the human counterpart, therefore, there is an interaction between the humans and robots. Interactions among humans are often taken for granted as, since children, we learn how to interact with each other. In robotics, this interaction is still very immature, however, critical for a successful incorporation of robots in society. Human robot interaction (HRI) is the domain that works on improving these interactions. HRI encloses many aspects, and a significant one is trust. Trust is the assumption that somebody or something is good and reliable; and it is critical for a developed society. Therefore, in a society where robots can part, the trust they could generate will be essential for cohabitation. A downside of trust is overtrusting an entity; in other words, an insufficient alignment of the projected trust and the expectations of a morally correct behaviour. This effect could negatively influence and damage the interactions between agents. In the case of humans, it is usually exploited by scammers, conmen or social engineers - who take advantage of the people's overtrust in order to manipulate them into performing actions that may not be beneficial for the victims. This thesis tries to shed light on the development of trust towards robots, how this trust could become overtrust and be exploited by social engineering techniques. More precisely, the following experiments have been carried out: (i) Treasure Hunt, in which the robot followed a social engineering framework where it gathered personal information from the participants, improved the trust and rapport with them, and at the end, it exploited that trust manipulating participants into performing a risky action. (ii) Wicked Professor, in which a very human-like robot tried to enforce its authority to make participants obey socially inappropriate requests. Most of the participants realized that the requests were morally wrong, but eventually, they succumbed to the robot'sauthority while holding the robot as morally responsible. (iii) Detective iCub, in which it was evaluated whether the robot could be endowed with the ability to detect when the human partner was lying. Deception detection is an essential skill for social engineers and professionals in the domain of education, healthcare and security. The robot achieved 75% of accuracy in the lie detection. There were also found slight differences in the behaviour exhibited by the participants when interacting with a human or a robot interrogator. Lastly, this thesis approaches the topic of privacy - a fundamental human value. With the integration of robotics and technology in our society, privacy will be affected in ways we are not used. Robots have sensors able to record and gather all kind of data, and it is possible that this information is transmitted via internet without the knowledge of the user. This is an important aspect to consider since a violation in privacy can heavily impact the trust. Summarizing, this thesis shows that robots are able to establish and improve trust during an interaction, to take advantage of overtrust and to misuse it by applying different types of social engineering techniques, such as manipulation and authority. Moreover, robots can be enabled to pick up different human cues to detect deception, which can help both, social engineers and professionals in the human sector. Nevertheless, it is of the utmost importance to make roboticists, programmers, entrepreneurs, lawyers, psychologists, and other sectors involved, aware that social robots can be highly beneficial for humans, but they could also be exploited for malicious purposes

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