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Proactive interaction management in domestic service robots to enhance human-robot conversational interaction

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dc.contributor.author Rajendran, H
dc.contributor.author Jayasekara, B
dc.date.accessioned 2023-12-29T05:54:18Z
dc.date.available 2023-12-29T05:54:18Z
dc.date.issued 2023
dc.identifier.issn 2815-0082 en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/22001
dc.description.abstract Robotics technology has long been renowned for its ability to handle com- plex, repetitive, and sometimes risky tasks that are impossible for humans. In industries, robots are preferred for precise operations in various manu- facturing stages of a product. On the other hand, domestic service robot is the other side of robotic technology that brings the smart robotic system into our homes. Service robots are specially designed to interact and assist humans where they provide a range of services, including caregiving, com- panionship, and entertainment. In addition, service robots can elevate living standards by assisting with essential daily activities, especially for people with disabilities. Nowadays, the incorporation of generative pretrained models in robotic sys- tems to provide a fluid conversation between humans and robots is a highly researched topic. Though pretrained generative language models can be incorporated into conversational systems, they often fail to offer healthy conversations with users. Most pretrained models are trained on billions of data points from blogs, posts, and forums, where language quality is not a concern. However, language quality and clarity matter greatly when de-signing robotic systems to interact with humans, especially the elderly and children en_US
dc.language.iso en en_US
dc.publisher University of Moratuwa en_US
dc.subject Robotics technology en_US
dc.title Proactive interaction management in domestic service robots to enhance human-robot conversational interaction en_US
dc.type Article-Full-text en_US
dc.identifier.year 2023 en_US
dc.identifier.journal Bolgoda Plains Research Magazine en_US
dc.identifier.issue 2 en_US
dc.identifier.volume 3 en_US
dc.identifier.pgnos pp.51-54 en_US
dc.identifier.doi https://doi.org/10.31705/BPRM.v3(2).2023.11 en_US


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