Multi-modal Personalisation in Long-Term Human-Robot Interaction
dc.contributor.author | Irfan, B | en |
dc.date.accessioned | 2020-12-04T22:24:09Z | |
dc.date.available | 2020-12-04T22:24:09Z | |
dc.date.issued | 2019-04-10 | en |
dc.identifier.uri | http://hdl.handle.net/10026.1/16710 | |
dc.description.abstract |
In the future, long-term human-robot interaction (HRI) will be integral in domestic applications, education, and rehabilitation. However, user engagement can decrease over time if the interaction is based on a fixed set of behaviours. Personalisation can improve user engagement and facilitate building rapport and trust by adapting to the user's personality, preferences or needs. This talk will touch on two approaches of personalisation in long-term HRI: user identification, and progress tracking for socially assistive robotics. | en |
dc.language.iso | en | en |
dc.title | Multi-modal Personalisation in Long-Term Human-Robot Interaction | en |
dc.type | Presentation | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
dc.publisher.place | Behaviors.AI workshop, Lyon, France | en |
dc.rights.embargoperiod | Not known | en |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | en |
rioxxterms.type | Other | en |