Aerial photography for 3D reconstruction in the Peruvian Highlands through a fixed-wing UAV system

Flores, Donate A.; Saito, Carlos; Paredes, Juan Augusto; Trujillano, Fedra

doi:10.1109/icmech.2017.7921137

Cited by 13 publications

(5 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In recent years, with the reduction in manufacturing costs, unmanned aerial vehicles (UAVs) have appeared in many applications. In the civil field, UAVs are widely used in aerial photography [1,2], smart agriculture [3,4], express transportation [5,6], disaster relief [7], observing wild animals [8], etc. In addition, due to the advantages of flexible and rapid deployment, UAVs are also suitable for various applications in fifth-generation (5G) and beyond wireless communications.…”

Section: Introductionmentioning

confidence: 99%

UAV Communication Recovery under Meteorological Conditions

Song

Huo

Liang

et al. 2023

Drones

View full text Add to dashboard Cite

Our study proposes a UAV communications recovery strategy under meteorological conditions based on a ray tracing simulation of excessive path loss in four distinct three-dimensional (3D) urban environments. We start by reviewing the air-to-ground propagation loss model under meteorological conditions, as well as the specific attenuation of rain, fog, and snow, and we propose a new expression for line-of-sight (LoS) probability. Using the two frequency bands of 28 GHz and 71 GHz, we investigate the impact of specific attenuation caused by different weather conditions and analyze the relationship between the radius of the UAV coverage area and the elevation angle. Furthermore, we investigate the effects of the rainfall rate, liquid water density, and snowfall rate on the maximum coverage area and optimal height of the UAV. Eventually, we propose a strategy that involves compensating for the maximum path loss and adjusting the UAV’s position to recover the coverage of the UAV to ground users. Our results show that rain has the greatest impact on the UAV’s coverage area and optimum height among the three types of weather conditions. For various weather conditions, relative to Region 1, the percentage reduction in the maximum coverage radius of Region 2 to Region 4 increases gradually, and the extent of each increase is approximately 10%. Moreover, after adding the compensated path loss, the coverage radius of the UAV in the four regions is restored to a value slightly larger than that before the rain. In addition, rain caused the greatest reduction in UAV coverage for suburban environments and the lowest for high-rise urban environments.

show abstract

Section: Introductionmentioning

confidence: 99%

UAV Communication Recovery under Meteorological Conditions

Song

Huo

Liang

et al. 2023

Drones

View full text Add to dashboard Cite

show abstract

“…The accuracy of orientation estimation plays a crucial role in enhancing the overall performance of drones. Numerous drone applications can benefit from accurate orientation estimation, including navigation, perception, autonomous flight, and task execution [1][2][3][4][5][6]. Firstly, improving the orientation precision in navigation applications can reduce the likelihood of unintended route deviation and ensure maritime safety in dynamic environments.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, by increasing the accuracy of orientation estimation, drones can substantially enhance the dependability and efficiency of autonomous flight and task completion. By approaching the target direction, drones can implement tasks more precisely, resulting in safer and more efficient operations for applications such as plant protection and aerial photography [5,6]. In summary, improving the precision of orientation estimation has significant practical value.…”

Section: Introductionmentioning

confidence: 99%

Trust–Region Nonlinear Optimization Algorithm for Orientation Estimator and Visual Measurement of Inertial–Magnetic Sensor

Jia

Wei

2023

Drones

View full text Add to dashboard Cite

This paper proposes a novel robust orientation estimator to enhance the accuracy and robustness of orientation estimation for inertial–magnetic sensors of the small consumer–grade drones. The proposed estimator utilizes a trust–region strategy within a nonlinear optimization framework, transforming the orientation fusion problem into a nonlinear optimization problem based on the maximum likelihood principle. The proposed estimator employs a trust–region Dogleg gradient descent strategy to optimize orientation precision and incorporates a Huber robust kernel to minimize interference caused by acceleration during the maneuvering process of the drone. In addition, a novel method for evaluating the performance of orientation estimators is also presented based on visuals. The proposed method consists of two parts: offline calibration of the basic cube using Augmented Reality University of Cordoba (ArUco) markers and online orientation measurement of the sensor carrier using a nonlinear optimization solver. The proposed measurement method’s accuracy and the proposed estimator’s performance are evaluated under low–dynamic (rotation) and high–dynamic (shake) conditions in the experiment. The experimental findings indicate that the proposed measurement method obtains an average re–projection error of less than 0.1 pixels. The proposed estimator has the lowest average orientation error compared to conventional orientation estimation algorithms. Despite the time–consuming nature of the proposed estimator, it exhibits greater robustness and precision, particularly in highly dynamic environments.

show abstract

“…With the development of aviation and aerospace industry and Internet technology, unmanned aerial vehicle (UAV) plays an important role in military reconnaissance and strike (Nex and Remondino, 2014), aerial photography (Flores et al, 2017), agricultural plant protection (Khan et al, 2019), police security (Li and Zhen, 2021), oilfield inspection (Ge et al, 2020), etc. Due to the increased difficulty of the task and the complexity of the environment, single UAV operations have been unable to meet the task requirements.…”

Section: Introductionmentioning

confidence: 99%

Cooperative 3D Path Planning of Multi-UAV Via Improved Fruit Fly Optimization

Mao

Huang

Qin

et al. 2021

Preprint

View full text Add to dashboard Cite

Path planning of multiple unmanned aerial vehicles (UAVs) is a crucial step in cooperative operation of multiple UAVs, whose main difficulties lie in the severe coupling of time and three-Dimensional (3D) space as well as the complexity of multi-objective optimization. For this purpose, the time stamp segmentation (TSS) model is first adopted to resolve the timespace coupling among multiple UAVs. Meanwhile, the solution space is reduced by transforming the multiobjective problem to a multi-constraint problem. In consequence, based on the elite retention strategy, a novel improved fruit fly optimization algorithm (NIFOA) is proposed for multi-UAV cooperative path planning, which overcomes the shortcomings of basic fruit fly optimization algorithm in slow convergence speed and the potentials to fall into local optima. In particular, the multi-subpopulations evolution mechanism is further designed to optimize the elite subpopulation. At last, the effectiveness of the proposed NIFOA has been verified by numerical experiments.

show abstract

Aerial photography for 3D reconstruction in the Peruvian Highlands through a fixed-wing UAV system

Cited by 13 publications

References 2 publications

UAV Communication Recovery under Meteorological Conditions

UAV Communication Recovery under Meteorological Conditions

Trust–Region Nonlinear Optimization Algorithm for Orientation Estimator and Visual Measurement of Inertial–Magnetic Sensor

Cooperative 3D Path Planning of Multi-UAV Via Improved Fruit Fly Optimization

Contact Info

Product

Resources

About