Open this publication in new window or tab >>2017 (English)In: Proceedings of the 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), IEEE, 2017, p. 13-18Conference paper, Published paper (Refereed)
Abstract [en]
In polar region operations, drift sea ice positioning and tracking is useful for both scientific and safety reasons. Modeling ice movements has proven difficult, not least due to the lack of information of currents and winds of high enough resolution. Thus, observations of drift ice is essential to an up-to-date ice-tracking estimate.
Recent years have seen the rise of Unmanned Aerial Systems (UAS) as a platform for geoobservation, and so too for the tracking of sea ice. Being a mobile platform, the research on UAS path-planning is extensive and usually involves an objective-function to minimize. For the purpose of observation however, the objective-function typically changes as observations are made along the path.
Further, the general problem involves multiple UAS and—in the case of sea ice tracking—vast geographical areas.
In this paper we discuss the architectural outline of a system capable of fusing data from multiple sources—UAS’s and others—as well as incorporating that data for both path-planning, sea ice movement prediction and target initialization. The system contains tracking of sea ice objects, situation map logic and is expandable as discussed with path-planning capabilities for closing the loop of optimizing paths for information acquisition.
Place, publisher, year, edition, pages
IEEE, 2017
Keywords
Ice Tracking, UAS, Sensor Fusion, Path Planning
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-141910 (URN)10.1109/RED-UAS.2017.8101636 (DOI)000427383700003 ()978-1-5386-0939-2 (ISBN)978-1-5386-0940-8 (ISBN)
Conference
The 4th Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), Linköping, Sweden, October 3-5, 2017
Projects
LINK-SIC
Funder
VINNOVA
Note
Funding agencies: European Unions Horizon research and innovation programme under the Marie Sklodowska-Curie grant [642153]; Research Council of Norway through the Centres of Excellence funding scheme [223254 - NTNU-AMOS]; Vinnova Industry Excellence Center LINK-SIC, the S
2017-10-132017-10-132018-04-11Bibliographically approved