Journal article
Adaptive Opportunistic Airborne Sensor Sharing
ACM transactions on autonomous and adaptive systems, Vol.13(1), pp.1-29
05/21/2018
DOI: 10.1145/3179994
Abstract
Airborne sensor platforms are becoming increasingly significant for both civilian and military operations; yet, at present, their sensors are typically idle for much of their flight time, e.g., while the sensor-equipped platform is in transit to and from the locations of sensing tasks. The sensing needs of many other potential information consumers might thus be served by sharing such sensors, thereby allowing other information consumers to opportunistically task them during their otherwise unscheduled time, as well as enabling other improvements, such as decreasing the number of platforms needed to achieve a goal and increasing the resilience of sensor tasks through duplication. We have implemented a prototype system realizing these goals in Mission-Driven Tasking of Information Producers (MTIP), which leverages an agent-based representation of tasks and sensors to enable fast, effective, and adaptive opportunistic sharing of airborne sensors. Using a simulated large-scale disaster-response scenario populated with publicly available Geographic Information System (GIS) datasets, we demonstrate that correlations in task location are likely to lead to a high degree of potential for sensor-sharing. We then validate that our implementation of MTIP can successfully carry out such sharing, showing that it increases the number of sensor tasks served, reduces the number of platforms required to serve a given set of sensor tasks, and adapts well to radical changes in flight path.
Details
- Title: Subtitle
- Adaptive Opportunistic Airborne Sensor Sharing
- Creators
- Jacob Beal - RTXKyle Usbeck - RTXJoseph Loyall - RTXMason Rowe - United States Air Force Research LaboratoryJames Metzler - United States Air Force Research Laboratory
- Resource Type
- Journal article
- Publication Details
- ACM transactions on autonomous and adaptive systems, Vol.13(1), pp.1-29
- Publisher
- Assoc Computing Machinery
- DOI
- 10.1145/3179994
- ISSN
- 1556-4665
- eISSN
- 1556-4703
- Number of pages
- 29
- Grant note
- FA8750-14-C-0096 / United States Air Force; United States Department of Defense
- Language
- English
- Date published
- 05/21/2018
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984627285602771
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