Internet-of-Things in motion: A UAV coalition model for remote sensing in smart cities
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Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI AG
Abstract
Unmanned aerial vehicles (UAVs) or drones are increasingly used in cities to provide
service tasks that are too dangerous, expensive or difficult for human beings. Drones are also used
in cases where a task can be performed more economically and or more efficiently than if done by
humans. These include remote sensing tasks where drones can be required to form coalitions by
pooling their resources to meet the service requirements at different locations of interest in a city.
During such coalition formation, finding the shortest path from a source to a location of interest is key
to efficient service delivery. For fixed-wing UAVs, Dubins curves can be applied to find the shortest
flight path. When a UAV flies to a location of interest, the angle or orientation of the UAV upon its
arrival is often not important. In such a case, a simplified version of the Dubins curve consisting of
two instead of three parts can be used. This paper proposes a novel model for UAV coalition and
an algorithm derived from basic geometry that generates a path derived from the original Dubins
curve for application in remote sensing missions of fixed-wing UAVs. The algorithm is tested by
incorporating it into three cooperative coalition formation algorithms. The performance of the model
is evaluated by varying the number of types of resources and the sensor ranges of the UAVs to reveal
the relevance and practicality of the proposed model.
Description
Keywords
Smart cities, Internet-of-Things, Multi-drone task allocation, Unmanned aerial vehicles, Path planning
Citation
Ismail, A., Bagula, B., & Tuyishimire, E. (2018). Internet-Of-Things in Motion: A UAV Coalition Model for Remote Sensing in Smart Cities. Sensors, 18(7), 2184. doi: 10.3390/s18072184