A multi-UAV cooperative route planning methodology for 3D fine-resolution building model reconstruction

Zheng, Xuan; Wang, Fei; Li, Zhanghua

doi:10.1016/j.isprsjprs.2018.11.004

Cited by 65 publications

(42 citation statements)

References 24 publications

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“…The problem was solved as a VRP, and the Yalmip toolbox and Gorubi solver were used to optimize the maximum flight time and the number of required UAVs. Zheng et al (2018) studied CPP for 3D fine-resolution building model reconstruction with the goal of improving the data-collection speed while minimizing redundant image datasets. This problem was formulated as a VRP and solved using the Yalmip toolbox and Gorubi solver.…”

Section: Classification Of Existing Researchmentioning

confidence: 99%

A review of cooperative path planning of an unmanned aerial vehicle group

Zhang

Xin

Dou

et al. 2020

Front Inform Technol Electron Eng

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As a cutting-edge branch of unmanned aerial vehicle (UAV) technology, the cooperation of a group of UAVs has attracted increasing attention from both civil and military sectors, due to its remarkable merits in functionality and flexibility for accomplishing complex extensive tasks, e.g., search and rescue, fire-fighting, reconnaissance, and surveillance. Cooperative path planning (CPP) is a key problem for a UAV group in executing tasks collectively. In this paper, an attempt is made to perform a comprehensive review of the research on CPP for UAV groups. First, a generalized optimization framework of CPP problems is proposed from the viewpoint of three key elements, i.e., task, UAV group, and environment, as a basis for a comprehensive classification of different types of CPP problems. By following the proposed framework, a taxonomy for the classification of existing CPP problems is proposed to describe different kinds of CPPs in a unified way. Then, a review and a statistical analysis are presented based on the taxonomy, emphasizing the coordinative elements in the existing CPP research. In addition, a collection of challenging CPP problems are provided to highlight future research directions.

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Section: Classification Of Existing Researchmentioning

confidence: 99%

A review of cooperative path planning of an unmanned aerial vehicle group

Zhang

Xin

Dou

et al. 2020

Front Inform Technol Electron Eng

View full text Add to dashboard Cite

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“…A SSESSMENTS of natural disasters and risk are the foundation of decision-making processes for a wide variety of actors from the public to government emergency managers. Quickly quantifying damage and expected future losses is usually the first step to becoming aware of the current situation [1]- [3]. The land use/land cover (LULC) products from remote sensing imagery can provide first-hand information for this purpose [4]- [6].…”

Section: Introductionmentioning

confidence: 99%

Full Parameter Time Complexity (FPTC): A Method to Evaluate the Running Time of Machine Learning Classifiers for Land Use/Land Cover Classification

Zheng

Jia

Guo

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Nowadays, the UAS take a huge market share for the aerial photography [30]- [32],and they are widely used for 3D reconstruction data capturing for disaster evaluation, cultural heritage protection, geological mapping, etc [7], [33], [34].…”

Section: Introductionmentioning

confidence: 99%

Adaptable Flight Line Planning for Airborne Photogrammetry Using DEM

Zhao

Zhang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Flight line planning is the first step in an aerial photography campaign. Its two key parameters, ground sampling distance (GSD) and overlap should be designed carefully as they will impact subsequent flying workload and even the final mapping accuracy. For a flat terrain region, flight line planning is easy using a traditional method with fixed baseline ,flight spacing and flight altitude. But for a steep terrain region, photo overlap and GSD will change greatly with topography, thus a flight line planning using the traditional method is not sufficient. This paper presents a novel adaptable flight line planning method for frame camera with four application modes. The flight line planning procedure is implemented through rigorous imaging geometry model using digital elevation data, where actual overlap and GSD can be calculated precisely. Using the desired overlap and GSD as constraint conditions, the flight spacing, baseline and flight altitude can be adjusted adaptively according to ground topography. To assess the effect, a hypothetical test in a rugged terrain region was conducted to compare the project workload, GSD and overlap of the four modes. The results show that Mode 2, Mode 3 and Mode 4 can realize better overlap with lower workload than the traditional method Mode 1. Mode 3 and Mode 4 have better GSD distribution than Mode 1 and Mode 2. The Mode 3 method was also validated in an actual project, showing a favorable performance in final reality 3D model result.

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A multi-UAV cooperative route planning methodology for 3D fine-resolution building model reconstruction

Cited by 65 publications

References 24 publications

A review of cooperative path planning of an unmanned aerial vehicle group

A review of cooperative path planning of an unmanned aerial vehicle group

Full Parameter Time Complexity (FPTC): A Method to Evaluate the Running Time of Machine Learning Classifiers for Land Use/Land Cover Classification

Adaptable Flight Line Planning for Airborne Photogrammetry Using DEM

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