Abstract
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).Citation
Jiang, Z. (2010) 'A statistical approach to a verb vector task classifier'. MSc by research thesis. University of Bedfordshire.Publisher
University of BedfordshireType
Thesis or dissertationLanguage
enDescription
A thesis submitted to the University of Bedfordshire, in fulfilment ofthe requirements for the degree of Master of Science by researchCollections
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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.
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