Considerations for Task Allocation in Human-Robot Teams
dc.contributor.author | Ali, Arsha | |
dc.contributor.author | Tilbury, Dawn | |
dc.contributor.author | Robert, Lionel Jr | |
dc.date.accessioned | 2022-10-06T12:00:39Z | |
dc.date.available | 2022-10-06T12:00:39Z | |
dc.date.issued | 2022-10-06 | |
dc.identifier.citation | Ali, A., Tilbury, D. and Robert, L. P. (2022). Considerations for Task Allocation in Human-Robot Teams, 2022 AAAI Fall Symposium on AI for HRI, Arlington, Virginia, November 17-19, 2022 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/174994 | en |
dc.description.abstract | In human-robot teams where agents collaborate together, there needs to be a clear allocation of tasks to agents. Task allocation can aid in achieving the presumed benefits of human-robot teams, such as improved team performance. Many task allocation methods have been proposed that include factors such as agent capability, availability, workload, fatigue, and task and domain-specific parameters. In this paper, selected work on task allocation is reviewed. In addition, some areas for continued and further consideration in task allocation are discussed. These areas include the level of collaboration, novel tasks, unknown and dynamic agent capabilities, negotiation and fairness, and ethics. Where applicable, we also mention some of our work on task allocation. Through continued efforts and considerations in task allocation, human-robot teaming can be improved. | en_US |
dc.description.sponsorship | Army Research Office Cooperative Agreement Number W911NF-21-2-0168 | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | 2022 AAAI Fall Symposium | en_US |
dc.subject | human-robot teaming | en_US |
dc.subject | human-robot interaction | en_US |
dc.subject | Task Allocation | en_US |
dc.subject | Human-Robot Teams | en_US |
dc.subject | Human-Robot Task Allocation | en_US |
dc.subject | task allocation methods | en_US |
dc.subject | agent capability | en_US |
dc.subject | Future of Work | en_US |
dc.subject | human-computer interaction | en_US |
dc.subject | AI Ethics | en_US |
dc.subject | AI Fairness | en_US |
dc.subject | robot trust | en_US |
dc.subject | human-robot team trust | en_US |
dc.subject | robot overtrust | en_US |
dc.subject | under robot trust | en_US |
dc.subject | undertrusting | en_US |
dc.subject | overtrusting | en_US |
dc.subject | calibrated trust | en_US |
dc.subject | calibrated robot trust | en_US |
dc.title | Considerations for Task Allocation in Human-Robot Teams | en_US |
dc.type | Conference Paper | en_US |
dc.subject.hlbsecondlevel | Information Science | |
dc.subject.hlbtoplevel | Social Sciences | |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Information, School of | en_US |
dc.contributor.affiliationum | Robotics Institute | en_US |
dc.contributor.affiliationum | Robotics Department | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/174994/1/AI_HRI_2022_final.pdf | |
dc.identifier.doi | https://dx.doi.org/10.7302/6543 | |
dc.identifier.source | 2022 AAAI Fall Symposium | en_US |
dc.identifier.orcid | 0000-0002-1410-2601 | en_US |
dc.description.filedescription | Description of AI_HRI_2022_final.pdf : Main File | |
dc.description.depositor | SELF | en_US |
dc.identifier.name-orcid | Robert, Lionel P.; 0000-0002-1410-2601 | en_US |
dc.working.doi | 10.7302/6543 | en_US |
dc.owningcollname | Information, School of (SI) |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.