TagTeam: Towards Wearable-Assisted, Implicit Guidance for Human–Drone Teams
| dc.contributor.author | Jayarajah, Kasthuri | |
| dc.contributor.author | Gangopadhyay, Aryya | |
| dc.contributor.author | Waytowich, Nicholas | |
| dc.date.accessioned | 2022-09-14T16:13:14Z | |
| dc.date.available | 2022-09-14T16:13:14Z | |
| dc.date.issued | 2022-08-10 | |
| dc.description | SmartWear '22: Proceedings of the 1st ACM Workshop on Smart Wearable Systems and Applications, October 2022 | |
| dc.description.abstract | The availability of sensor-rich smart wearables and tiny, yet capable, unmanned vehicles such as nano quadcopters, opens up opportunities for a novel class of highly interactive, attention-shared human–machine teams. Reliable, lightweight, yet passive exchange of intent, data and inferences within such human–machine teams make them suitable for scenarios such as search-and-rescue with significantly improved performance in terms of speed, accuracy and semantic awareness. In this paper, we articulate a vision for such human–drone teams and key technical capabilities such teams must encompass. We present TagTeam, an early prototype of such a team and share promising demonstration of a key capability (i.e., motion awareness). | en_US |
| dc.description.sponsorship | We acknowledge the support of the U.S. Army Grant No. W911NF21- 20076. | en_US |
| dc.description.uri | https://dl.acm.org/doi/abs/10.1145/3556560.3560715 | |
| dc.format.extent | 6 pages | en_US |
| dc.genre | journal articles | en_US |
| dc.genre | preprints | en_US |
| dc.genre | conference papers and proceedings | |
| dc.identifier | doi:10.13016/m2khsk-3dhg | |
| dc.identifier.citation | Jayarajah, Kasthuri, Aryya Gangopadhyay, and Nicholas Waytowich. “TagTeam: Towards Wearable-Assisted, Implicit Guidance for Human-Drone Teams.” In Proceedings of the 1st ACM Workshop on Smart Wearable Systems and Applications, 13–18. SmartWear ’22. New York, NY, USA: Association for Computing Machinery, 2022. https://doi.org/10.1145/3556560.3560715. | |
| dc.identifier.uri | https://doi.org/10.1145/3556560.3560715 | |
| dc.identifier.uri | http://hdl.handle.net/11603/25663 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | ACM | |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Information Systems Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.rights | This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. | en_US |
| dc.rights | Public Domain Mark 1.0 | * |
| dc.rights.uri | http://creativecommons.org/publicdomain/mark/1.0/ | * |
| dc.title | TagTeam: Towards Wearable-Assisted, Implicit Guidance for Human–Drone Teams | en_US |
| dc.type | Text | en_US |