Assisting Service Robots on their Journey to become Autonomous Agents: From Apprentice to Master by Participatory Observation
dc.contributor.author | Golchinfar, David | |
dc.contributor.author | Vaziri, Daryoush | |
dc.contributor.author | Stevens, Gunnar | |
dc.contributor.author | Schreiber, Dirk | |
dc.contributor.editor | Alt, Florian | |
dc.contributor.editor | Bulling, Andreas | |
dc.contributor.editor | Döring, Tanja | |
dc.date.accessioned | 2019-08-22T04:36:26Z | |
dc.date.available | 2019-08-22T04:36:26Z | |
dc.date.issued | 2019 | |
dc.description.abstract | Natural and reliable application of service robots (SR) in service domains, for instance health service or elderly care, is currently not possible and full autonomy and automatization of SR is still in far distance. Hence, methodologies are needed that promote human-robot collaboration and allow the robot to learn from its human mentor to become more autonomous and reliable. This demo illustrates an environment for such human-robot collaboration that provides an infrastructure for SR manipulation and teaching. The basic idea is that the robot becomes an apprentice that learns new skills by observing a trained human mentor that performs relevant tasks in the service domain by operating the robot. By observation and collaboration, the SR gradually becomes more autonomous and capable to carry out relevant healthcare tasks. | en |
dc.description.uri | https://dl.acm.org/authorize?N681350 | |
dc.identifier.doi | 10.1145/3340764.3345374 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/24554 | |
dc.language.iso | en | |
dc.publisher | ACM | |
dc.relation.ispartof | Mensch und Computer 2019 - Tagungsband | |
dc.relation.ispartofseries | Mensch und Computer | |
dc.subject | Service robot | |
dc.subject | healthcare | |
dc.subject | design | |
dc.subject | autonomous systems | |
dc.subject | machine learning | |
dc.subject | evolutionary development | |
dc.title | Assisting Service Robots on their Journey to become Autonomous Agents: From Apprentice to Master by Participatory Observation | en |
dc.type | Text/Conference Paper | |
gi.citation.publisherPlace | New York | |
gi.conference.date | 8.-11. September 2019 | |
gi.conference.location | Hamburg | |
gi.conference.sessiontitle | MCI: Interactive Demos | |
gi.document.quality | digidoc |