Bargaining Model-Based Coverage Area Subdivision of Multiple UAVs in Remote Sensing
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ORIGINAL ARTICLE
Bargaining Model-Based Coverage Area Subdivision of Multiple UAVs in Remote Sensing Jaehwi Seol 1
&
Hyoung Il Son 1
Received: 28 February 2020 / Revised: 28 May 2020 / Accepted: 28 May 2020 # The Korean Society for Agricultural Machinery 2020
Abstract Purpose Unmanned aerial vehicles (UAVs) have recently been used for remote sensing because they can fly from low to relatively high altitudes along a planned route and obtain the corresponding resolutions. In remote sensing, the limitations of a single UAV become more apparent as the size of the exploration area increases. In such situations, a multi-UAV setup is required, along with appropriate task allocation and area subdivision. Methods In this study, we propose area segmentation based on Rubinstein’s bargaining model for subdivision of coverage area among multiple UAVs for remote sensing. Results The negotiation between the two agents and the division of the territory among the three agents according to the field of view (FOV) of the UAVs were elucidated; the experiments were conducted with satellite images obtained from Google Maps. Conclusions For remote sensing using multiple UAVs, we proposed an area segmentation method using weak cooperation. The segmentation was based on the Rubinsteind route and obtain the correspondiended to two as well as three agents. Keywords Area subdivision . Multi-robot system . Negotiation . Rubinsteinplebargaining model . Task allocation . Unmanned aerial vehicle
Introduction Remote sensing primarily employs aerial images obtained using satellites, aircraft, etc. Aerial images obtained using satellites and aircraft are of relatively low resolutions; moreover, the frequency of observation and image use is low, which makes it difficult to obtain more accurate information. In addition, when the area of exploration is small, the use of satellites and aircraft is not cost-effective, which ultimately results in low-resolution images being obtained. Unmanned aerial vehicles (UAVs) can fly from low to relatively high altitudes along a planned route and obtain the corresponding resolutions. Thus, UAVs are more efficient in terms of both cost and resolution when compared with satellites and aircraft; as such, they are used significantly in remote sensing (Niethammer et al. 2012; Matese et al. 2012; Kim et al. 2019). * Hyoung Il Son [email protected] 1
Department of Rural and Biosystems Engineering, Chonnam National Universtiy, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Republic of Korea
The area that a single UAV can handle is limited by its battery capacity; the size of the area is also limited by the time required to process it. Therefore, as the size of an exploration area increases, the limitations of a single UAV become more pronounced, and its efficiency decreases. Thus, an expansion to a multi-UAV setup is required. Multi-robot systems (MRS) present considerable advantages over single robot systems. These advantages include the ability to resolve more complex tasks, super
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