Resource aware and incremental mosaics of wide areas from small-scale UAVs

Wischounig-Strucl, Daniel; Rinner, Bernhard

doi:10.1007/s00138-015-0699-5

Cited by 18 publications

(6 citation statements)

References 26 publications

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“…They explicitly discuss coverage optimisation methods and drone deployment strategies, although the two topics are separated: surveyed coverage‐oriented methods are mostly focused on PTZ camera networks (in which the camera cannot translate), while the analysed drone reconfiguration works are more focused on resource management (e.g. as in [11, 12]).…”

Section: Related Workmentioning

confidence: 99%

Drone swarm patrolling with uneven coverage requirements

Piciarelli

Foresti

2020

IET Computer Vision

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Swarms of drones are being more and more used in many practical scenarios, such as surveillance, environmental monitoring, search and rescue in hardly-accessible areas, etc.. While a single drone can be guided by a human operator, the deployment of a swarm of multiple drones requires proper algorithms for automatic task-oriented control. In this paper, we focus on visual coverage optimization with drone-mounted camera sensors. In particular, we consider the specific case in which the coverage requirements are uneven, meaning that different parts of the environment have different coverage priorities. We model these coverage requirements with relevance maps and propose a deep reinforcement learning algorithm to guide the swarm. The paper first defines a proper learning model for a single drone, and then extends it to the case of multiple drones both with greedy and cooperative strategies. Experimental results show the performance of the proposed method, also compared with a standard patrolling algorithm.

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Section: Related Workmentioning

confidence: 99%

Drone swarm patrolling with uneven coverage requirements

Piciarelli

Foresti

2020

IET Computer Vision

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“…[19] have developed methods for real‐time mosaicing of aerial images captured by UAVs. Wischounig‐Strucl and Rinner [20] have used a system of multiple networked UAVs for incremental mosaicing of wide areas. Caballero et al .…”

Section: Related Workmentioning

confidence: 99%

“…Botterill et al [18] and Kekec et al [19] have developed methods for real-time mosaicing of aerial images captured by UAVs. Wischounig-Strucl and Rinner [20] have used a system of multiple networked UAVs for incremental mosaicing of wide areas. Caballero et al [21,22] have used online mosaicing for improving the localisation of UAVs based on homographies computed from successive images.…”

Section: Related Workmentioning

confidence: 99%

Mosaicing of multiplanar regions through autonomous navigation of off‐the‐shelf quadcopter

Prasad

Akula

Vemula

et al. 2019

IET cyber-systems robotics

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“…The graphic data gained from a low ceiling are widely used in making the stock-taking of the power lines, surveillance, production of high-resolution orthophoto, and in 3D modelling of the building and cities. Thanks to delivering spatial and time high resolution of images, it is also possible to make current and exact map analysis ( Remondino et al, 2011, Saari et al, 2011, Nex and Remondino,2014Wischounig-Strucl and Rinner, 2015). In progress of the continuous development of the non-symmetrical digital cameras, miniaturization of the unmanned aerial vehicles, and automatization of making the orthophotos, the photogrammetry of the low ceiling becomes more widely used.…”

Section: Introductionmentioning

confidence: 99%

Chosen Aspects of the Production of the Basic Map Using Uav Imagery

Kędzierski¹,

Fryśkowska²,

Wierzbicki³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission ICWG I/VbKEY WORDS: Photogrammetry, Unmanned Aerial Vehicle, Orthoimage, Geodesy, Mapping ABSTRACT:For several years there has been an increasing interest in the use of unmanned aerial vehicles in acquiring image data from a low altitude. Considering the cost-effectiveness of the flight time of UAVs vs. conventional airplanes, the use of the former is advantageous when generating large scale accurate ortophotos. Through the development of UAV imagery, we can update largescale basic maps. These maps are cartographic products which are used for registration, economic, and strategic planning. On the basis of these maps other cartographic maps are produced, for example maps used building planning. The article presents an assessesment of the usefulness of orthophotos based on UAV imagery to upgrade the basic map. In the research a compact, nonmetric camera, mounted on a fixed wing powered by an electric motor was used. The tested area covered flat, agricultural and woodland terrains. The processing and analysis of orthorectification were carried out with the INPHO UASMaster programme. Due to the effect of UAV instability on low-altitude imagery, the use of non-metric digital cameras and the low-accuracy GPS-INS sensors, the geometry of images is visibly lower were compared to conventional digital aerial photos (large values of phi and kappa angles). Therefore, typically, low-altitude images require large along-and across-track direction overlap -usually above 70 %. As a result of the research orthoimages were obtained with a resolution of 0.06 meters and a horizontal accuracy of 0.10m. Digitized basic maps were used as the reference data. The accuracy of orthoimages vs. basic maps was estimated based on the study and on the available reference sources. As a result, it was found that the geometric accuracy and interpretative advantages of the final orthoimages allow the updating of basic maps. It is estimated that such an update of basic maps based on UAV imagery reduces processing time by approx. 40%.

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Resource aware and incremental mosaics of wide areas from small-scale UAVs

Cited by 18 publications

References 26 publications

Drone swarm patrolling with uneven coverage requirements

Drone swarm patrolling with uneven coverage requirements

Mosaicing of multiplanar regions through autonomous navigation of off‐the‐shelf quadcopter

Chosen Aspects of the Production of the Basic Map Using Uav Imagery

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