Yes / Service robots with advanced intelligence capabilities can potentially transform servicescapes. However, limited attention has been given to how consumers experiencing vulnerabilities, particularly those with disabilities, envisage the characteristics of robots’ prospective integration into emotionally intense servicescapes, such as long-term care (LTC). We take an interdisciplinary approach conducting three exploratory studies with consumers with disabilities involving Community Philosophy, LEGO® Serious Play®, and Design Thinking methods. Addressing a lack of consumer-centric research, we offer a three-fold contribution by 1) developing a conceptualization of consumer-conceived value of robots in LTC, which are envisaged as a supporting resource offering consumers opportunities to realize value; 2) empirically evidencing pathogenic vulnerabilities as a potential value-destruction factor to underscore the importance of integrating service robots research with a service inclusion paradigm; and 3) providing a theoretical extension and clarification of prior characterizations of robots’ empathetic and emotion-related AI capabilities. Consumers with disabilities conceive robots able to stimulate and regulate emotions by mimicking cognitive and behavioral empathy, but unable to express affective and moral empathy, which is central to care experience. While providing support for care practices, for the foreseeable future, service robots will not, in themselves, actualize the experience of “being cared for.” / This paper originates as a result of work on a project titled “Improving Inclusivity in Robotics Design” which received funding from “Research England, via The University of Sheffield’s Higher Education Innovation Fund (HEIF)" and in-kind funding from IBM.

Yes / Cost-saving and sanitation considerations and the challenge of labor shortages have catalyzed the application of service robots in restaurants. Although service robots can perform multiple roles and functions, more research attention is needed in hospitality contexts on how different combinations of using robots and humans at different product/service layers may influence customers’ experiences and behavioral intentions. Building on the literature of product level theory and authenticity, this study empirically investigated this issue with data collected from 364 customers in China. The results show that the use of robots in core and facilitating product levels is less effective in improving consumers’ perceived service and brand authenticity. Consumers’ perceived service authenticity positively influences their brand authenticity and repurchase intention. Consumers’ perceived brand authenticity only positively affects their repurchase intention. Both theoretical and managerial implications are discussed in this paper. / Research Development Fund Publication Prize Award winner, July 2022

The following documents a research through design inquiry into how socialites of a hospital environment are disrupted or improved by implementing a service robot. The robot, support for excessive work, represents a new intermediary between a patient and a caregiver. Robotic work routines appear as better, more efficient, and more affordable. Apart from other ethical and inclusive considerations given to this dialogue, the social values hidden in traditional workflows are of equal importance.  This thesis attempts to generate constructive design research about emergent social norms and social dynamics caused by service robots’ implementation. The lessons learned are presented in a final research discussion. Further applied, the knowledge held common grounds with a rehabilitation robot developed by Blue Ocean Robotics.

With the ongoing progress of research in robotics, computer vision and artificial intelligence, robots are becoming more complex, their functionalities are increasing and their abilities to solve particular problems get more efficient. For these robots to share with us our lives and environment, they should be able to move autonomously and be operated easily by users. The main focus of this thesis is on the differences and similarities in a human to a human versus a human to a robot interaction in an office environment. Experimental methods are used to identify these differences and similarities and arrive at an understanding about how users perceive robots and the robots’ abilities to help in the development of interactive service robots that are able to navigate and perform various tasks in a real life environment. A user study was conducted where 14 subjects were observed while presenting an office environment to a mobile robot and then to a person. The results from this study were that users used the same verbal phrases, hand gestures, gaze, etc. to present the environment to the robot versus a person but they emphasized more by identifying the different items to the robot .The subjects took less time to show a person around than the robot. / Genom forskning i robotik, datorseende och artificiell intelligens kommer robotar att bli mer och mer komplexa. Robotars funktionalitet ökar ständigt och deras kapacitet att lösa specifika problem blir mer effektiv. För att dessa robotar ska finnas i våra vardagsliv och vår miljö måste de kunna röra sig självständigt (autonomt) och de måste vara lätta att hantera för användare. Detta examensarbete fokuserar på skillnader och likheter mellan interaktion människa - människa och robot - människa i en kontorsmiljö. Med hjälp av experimentell metod är det möjligt att upptäcka dessa skillnader och likheter och därmed förstå hur människor uppfattar robotar och deras förmåga. Detta kan bidra till utvecklingen av servicerobotar som kan navigera och utföra olika uppgifter i vardagslivet. En användarstudie utfördes med 14 försökspersoner som observerades medan de presenterade en kontorsmiljö både för en människa och för en robot. Resultatet av denna studie var att försökspersonerna använde samma typer av muntliga uttryck och handgester, blickar, osv. för att presentera miljön för en människa som för roboten. De uttryckte sig mer detaljerat för roboten när det gällde att identifiera olika föremål i miljön. Försökspersonerna behövde mer tid för att presentera miljön för roboten än en människa.

A Robótica tem iniciado uma transição de Robótica Industrial para Robótica de Serviço, movendo-se em direção as necessidades diárias dos seres humanos. Para realizar essa transição, robôs necessitam de mais autonomia para executar tarefas em espaços dinâmicos ocupados por humanos, diferente dos ambientes controlados das fábricas. Nesta tese, é investigado um problema no qual um time de robôs completamente autônomos deve visitar certos locais em um ambiente interno usado por humanos a fim de executar algum tipo de tarefa. Este problema está relacionado a três importantes questões da Robótica e Inteligência Artificial (IA), que são: coordenação, localização e navegação. Para coordenar as visitas nos locais desejados, um escalonamento deve ser realizado para encontrar as rotas para os robôs. Tal escalonamento deve minimizar a distância total viajada pelo time e também balancear as rotas. Este problema pode ser modelado como sendo uma instância do Problema dos Múltiplos Caixeiros Viajantes (PMCV). Como este problema é classificado como NP-Difícil, é proposto o uso de algoritmos aproximados para encontrar soluções satisfatórias para o problema. Uma vez que as rotas estão computadas, os robôs necessitam de se localizar no ambiente para que eles tenham certeza de que estão visitando os lugares corretos. Muitas técnicas de localização não são muito precisas em ambientes internos devido a diferentes tipos de ruídos. Desta forma, é proposto uma combinação de duas delas. Nesta abordagem, um algoritmo de localização WiFi rastreia a localização global do robô, enquanto um algoritmo de localização Kinect estima sua posição atual dentro da área delimitada pela localização global. Depois de visitar um dado local de sua rota, o robô deve navegar em direção ao próximo. A navegação em ambientes internos ocupados por humanos é uma tarefa difícil, uma vez que muitos objetos móveis e dinâmicos podem ser encontrados no caminho. Para isso, o robô deve possuir controles reativos para evitar colidir com objetos dinâmicos, como pessoas, enquanto ele navega. Além disso, objetos móveis, como mobílias, são passíveis de serem movidos frequentemente, o que muda o mapa utilizado para planejar o caminho do robô. Para resolver estes problemas, é proposto um algoritmo de desvio de obstáculos e um planejador dinâmico de caminho para ambientes internos ocupados por humanos. Desta forma, esta tese contribui com uma série de algoritmos para os problemas de coordenação, localização e navegação. São introduzidos: Algoritmos Genéticos (AGs) multi-objetivo para resolver o Problema dos Múltiplos Caixeiros Viajantes, abordagens de localização que utilizam a técnica de Filtro de Partículas (FP) com dispositivos Kinect e WiFi, um Sistema Híbrido Inteligente (SHI) baseado em Lógica Fuzzy (LF) e Redes Neuronais Artificiais (RNA) para desvio de obstáculos e uma adaptação do algoritmo D*Lite que permite o robô replanejar caminhos de forma eficiente e requisitar auxílio humano se necessário. Todos os algoritmos são avaliados em robôs reais e simuladores, demonstrando seus desempenhos em resolver os problemas abordados nesta tese. / Robotics has started the transition from industrial into service robotics, moving closer towards humans daily needs. To accomplish this transition, robots require more autonomy to perform tasks in dynamic spaces occupied by humans, different from well controlled environments of factory floors. In this thesis, we investigate a problem in which a team of completely autonomous robots needs to visit certain locations in an indoor human environment in order to perform some kind of task. This problem is related to three important issues of Robotics and \ac{AI}, namely: coordination, localization and navigation. To coordinate the visits in the desired locations, a scheduling must be performed to find routes for the robots. Such scheduling needs to minimize the total distance traveled by the team and also to balance the routes. We model this problem as being an instance of the multiple Traveling Salesmen Problem (mTSP). Since it is classified as NP-Hard, we propose the use of approximation algorithms to find reasonable solutions to the problem. Once the routes are computed, the robots need to localize themselves in the environment so they can be sure that they are visiting the right places. Many localization techniques are not very accurate in indoor human environments due to different types of noise. Therefore, we propose the combination of two of them. In such approach, a WiFi localization algorithm tracks the global location of the robot while a Kinect localization algorithm estimates its current pose on that area. After visiting a given location of its route, the robot must navigate towards the next one. Navigation in indoor human environments is a challenging task as many moving and movable objects can be found in the way. The robot should be equipped with a reactive controller to avoid colliding with moving objects, like people, while it is navigating. Also, movable objects, such as furniture, are likely to be moved frequently, which changes the map used to plan the robot's path. To tackle these problems, we introduce an obstacle avoidance algorithm and a dynamic path planner for navigation in indoor human environments. We contribute a series of algorithms for the problems of coordination, localization, and navigation. We introduce: multi-objective Genetic Algorithms (GAs) to solve the mTSP, localization approaches that use Particle Filters (PFs) with Kinect and WiFi devices, a Hybrid Intelligent System (HIS) based on Fuzzy Logic (FL) and Artificial Neural Network (ANN) for obstacle avoidance, and an adaptation to the D*Lite algorithm that enables robots to replan paths efficiently and also ask for human assistance if it is necessary. All algorithms are evaluated on real robots and simulators, demonstrating their performances to solve the problems addressed in this thesis. / Tese (Doutorado)

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