Outline of a System for Integrated Adaptive Ice Tracking and Multi-Agent Path Planning
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...
| Published in: | 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS) |
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| Main Authors: | , , , |
| Format: | Book Part |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2017
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| Subjects: | |
| Online Access: | http://hdl.handle.net/11250/2471096 https://doi.org/10.1109/RED-UAS.2017.8101636 |
| Summary: | 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. acceptedVersion © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
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