Methods of Predicting the Heading, Pitch and Roll Angles for an Unmanned Aerial Vehicle

Wierzbicki, Damian; Krasuski, Kamil

doi:10.26552/com.c.2020.2.52-59

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…One such application is low-altitude imaging for photogrammetric and remote sensing studies. Relatively low costs of procurement and operation made this technology extremely popular [1,2]. However, still up to this day, there are UAVs (Unmanned Aerial Vehicles) available on the market that are equipped with single-frequency GPS (Global Positioning System) receivers, which allow the UAV's position to be determined with an accuracy of only just better than 10 m [3,4].…”

Section: Introductionmentioning

confidence: 99%

Application the SBAS/EGNOS Corrections in UAV Positioning

Krasuski¹,

Wierzbicki²

2021

Energies

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The paper presents a new concept of determining the resultant position of a UAV (Unmanned Aerial Vehicle) based on individual SBAS (Satellite-Based Augmentation System) determinations from all available EGNOS (European Geostationary Navigation Overlay Service) satellites for the SPP (Single Point Positioning) code method. To achieve this, the authors propose a weighted mean model to integrate EGNOS data. The weighted model was based on the inverse of the square of the mean position error along the component axes of the BLh ellipsoidal frame. The calculations included navigation data from the EGNOS S123, S126, S136 satellites. In turn, the resultant UAV position model was determined using the Scilab v.6.0.0 software. Based on the proposed computational strategy, the mean values of the UAV BLh coordinates’ standard deviation were better than 0.2 m (e.g., 0.0000018° = 0.01″ in angular measurement). Additionally, the numerical solution used made it possible to increase the UAV’s position accuracy by about 29% for Latitude, 46% for Longitude and 72% for ellipsoidal height compared to the standard SPP positioning in the GPS receiver. It is also worth noting that the standard deviation of the UAV position calculated from the weighted mean model improved by about 21 ÷ 50% compared to the arithmetic mean model’s solution. It can be concluded that the proposed research method allows for a significant improvement in the accuracy of UAV positioning with the use of EGNOS augmentation systems.

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Section: Introductionmentioning

confidence: 99%

Application the SBAS/EGNOS Corrections in UAV Positioning

Krasuski¹,

Wierzbicki²

2021

Energies

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“…It must be noted that the quality of a photogrammetric study is affected by many factors, the specific division of which can be found in paper [23]. The most important factors include: object shape and colour [24,25], image quality [26], used software, methods [22,27], used sensors [28], accuracy of support systems [29][30][31][32] and data fusion methods [33][34][35], sensor orientation [1] or even the sensor's temperature [36]. In this study, we focus only on the illumination of 3D urban mock-up lighting scene(s).…”

Section: Introductionmentioning

confidence: 99%

Seven Different Lighting Conditions in Photogrammetric Studies of a 3D Urban Mock-Up

et al. 2021

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One of the most important elements during photogrammetric studies is the appropriate lighting of the object or area under investigation. Nevertheless, the concept of “adequate lighting” is relative. Therefore, we have attempted, based on experimental proof of concept (technology readiness level—TRL3), to verify the impact of various types of lighting emitted by LED light sources for scene illumination and their direct influence on the quality of the photogrammetric study of a 3D urban mock-up. An important issue in this study was the measurement and evaluation of the artificial light sources used, based on illuminance (E), correlated colour temperature (CCT), colour rendering index (CRI) and Spectral power distribution (SPD) and the evaluation of the obtained point clouds (seven photogrammetric products of the same object, developed for seven different lighting conditions). The general values of the quality of the photogrammetric studies were compared. Additionally, we determined seventeen features concerning the group of tie-points in the vicinity of each F-point and the type of study. The acquired traits were related to the number of tie-points in the vicinity, their luminosities and spectral characteristics for each of the colours (red, green, blue). The dependencies between the identified features and the obtained XYZ total error were verified, and the possibility of detecting F-points depending on their luminosity was also analysed. The obtained results can be important in the process of developing a photogrammetric method of urban lighting monitoring or in selecting additional lighting for objects that are the subject of a short-range photogrammetric study.

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Drone Control using the Coupling of the PID Controller and Genetic Algorithm

Elajrami¹,

Satla²,

Bendine³

2021

Komunikácie

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Due to their strong abilities and easy usage, unmanned aerial vehicles (UAVs) commonly named drones have found a place and merged in the different industrial sectors. These varieties of applications encourage researchers to search for new control algorithms that make drones operate smoothly. In this regard, the present study mains to design a PID controller for four motors drones (quadcopter). For this purpose, a state-space representation of the drone is proposed based on Newton Euler's formularies for a rigid body. For better performance of the control algorithm (PID) the parameters Kp, Ki, and Kd for the controller are established using an optimization search schema based on a genetic algorithm. Various simulations were performed to test the proposed idea.

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Methods of Predicting the Heading, Pitch and Roll Angles for an Unmanned Aerial Vehicle

Cited by 3 publications

References 8 publications

Application the SBAS/EGNOS Corrections in UAV Positioning

Application the SBAS/EGNOS Corrections in UAV Positioning

Seven Different Lighting Conditions in Photogrammetric Studies of a 3D Urban Mock-Up

Drone Control using the Coupling of the PID Controller and Genetic Algorithm

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