Inclusion of service robots in the daily lives of frail older users: a step-by-step definition procedure on users' requirements
AffiliationMatia Instituto, Madrid
University of Santiago de Compostela
Dublin City University
Fondazione Don Carlo Gnocchi Onlus, Milano
Cardiff School of Engineering
University of Bedfordshire
user centred design
H670 Robotics and Cybernetics
MetadataShow full item record
Other TitlesRobots in older users’ daily lives
AbstractThe implications for the inclusion of robots in the daily lives of frail older adults, especially in relation to these population needs, have not been extensively studied. The “Multi-Role Shadow Robotic System for Independent Living” (SRS) project has developed a remotelycontrolled, semi-autonomous robotic system to be used in domestic environments. The objective of this paper is to document the iterative procedure used to identify, select and prioritize user requirements. Seventy-four requirements were identified by means of focus groups, individual interviews and scenario-based interviews. The list of user requirements, ordered according to impact, number and transnational criteria, revealed a high number of requirements related to basic and instrumental activities of daily living, cognitive and social support and monitorization, and also involving privacy, safety and adaptation issues. Analysing and understanding older users’ perceptions and needs when interacting with technological devices adds value to assistive technology and ensures that the systems address currently unmet needs.
CitationGarcía-Soler A, Facal D, Díaz-Orueta U, Pigini L, Blasi L, Qiu R (2017) 'Inclusion of service robots in the daily lives of frail older users: a step-by-step definition procedure on users' requirements', Archives of Gerontology and Geriatrics 74, pp.191-196.
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Test moment determination design in active robot learningZhao, Danchen (University of Bedfordshire, 2009-11)In recent years, service robots have been increasingly used in people's daily live. These robots are autonomous or semiautonomous and are able to cooperate with their human users. Active robot learning (ARL) is an approach to the development of beliefs for the robots on their users' intention and preference, which is needed by the robots to facilitate the seamless cooperation with humans. This approach allows a robot to perform tests on its users and to build up the high-order beliefs according to the users' responses. This study carried out primary research on designing the test moment determination component in ARL framework. The test moment determination component is used to decide right moment of taking a test action. In this study, an action plan theory was suggested to synthesis actions into a sequence, that is, an action plan, for a given task. All actions are defined in a special format of precondition, action, post-condition and testing time. Forward chaining reasoning was introduced to establish connection between the actions and to synthesis individual actions into an action plan, corresponding to the given task. A simulation environment was set up where a human user and a service robot were modelled using MATLAB. Fuzzy control was employed for controlling the robot to carry out the cooperative action. In order to examine the effect of test moment determination component, simulations were performed to execute a scenario where a robot passes on an object to a human user. The simulation results show that an action plan can be formed according to provided conditions and executed by simulated models properly. Test actions were taken at the moment determined by the test moment determination component to find the human user's intention.
Embedding ethics in the design of culturally competent socially assistive robotsBattistuzzi, Linda; Sgorbissa, Antonio; Papadopoulos, Chris; Papadopoulos, Irena; Koulouglioti, Christina; University of Genoa; University of Bedfordshire; Middlesex University (Institute of Electrical and Electronics Engineers Inc., 2019-01-07)Research focusing on the development of socially assistive robots (SARs) for the care of older adults has grown in recent years, prompting a great deal of ethical analysis and reflection on the future of SARs in caring roles. Much of this ethical thinking, however, has taken place far from the settings where technological innovation is practiced. Different frameworks have been proposed to bridge this gap and enable researchers to handle the ethical dimension of technology from within the design and development process, including Value Sensitive Design (VSD). VSD has been defined as a 'theoretically grounded approach to the design of technology that accounts for human values in a principled and comprehensive manner throughout the design process'. Inspired in part by VSD, we have developed a process geared towards embedding ethics at the core of CARESSES, an international multidisciplinary project that aims to design the first culturally competent SAR for the care of older adults. Here we describe that process, which included extracting key ethical concepts from relevant ethical guidelines and applying those concepts to scenarios that describe how the CARESSES robot will interact with individuals belonging to different cultures. This approach highlights the ethical implications of the robot's behavior early in the design process, thus enabling researchers to identify and engage with ethical problems proactively.
A statistical approach to a verb vector task classifierJiang, ZiPeng (University of Bedfordshire, 2010-11)How to enable a service robot to understand its user's intention is a hot topic of research today. Based on its understanding, the robot can coordinate and adjust its behaviours to provide desired assistance and services to the user as a capable partner. Active Robot Learning (ARL) is an approach to the development of the understanding of human intention. The task action bank is part of the ARL which can store task categories. In this approach, a robot actively performs test actions in order to obtain its user's intention from the user's response to the action. This thesis presents an approach to verbs clustering based on the basic action required of the robot, using a statistical method. A parser is established to process a corpus and analyse the probability of the verb feature vector, for example when the user says "bring me a cup of coffee", this means the same as "give me a cup of coffee". This parser could identify similar verbs between "bring" and "give" with the statistical method. Experimental results show the collocation between semantically related verbs, which can be further utilised to establish a test action bank for Active Robot Learning (ARL).