Urgent problems of UAV navigation system development and practical implementation

Харченко, Володимир Петрович; Kondratyuk, V. M.; Ilnytska, Svitlana; Kutsenko, Oleksandr; Larin, V. B.

doi:10.1109/apuavd.2013.6705313

Cited by 13 publications

(2 citation statements)

References 5 publications

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“…Unmanned aerial vehicles (UAVs) or drones are characterized by low cost and ease of operation, which leads to broad prospects for their use for remote sensing, mapping, monitoring and other civilian applications [1] - [4].…”

Section: Introduction and Problem Statementmentioning

confidence: 99%

Experimental Research of Integrated Navigation Systems in Problems of Quadrotor Path Tracking

Kondratiuk

Ilnytska

Kutsenko

et al. 2022

ECS

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The article deals deals with experimental research of the integrated navigation, guidance, and control system of quadrotor. The mathematical grounds of the study of the system are represented. Algorithm of functioning the integrated system is represented. Equations of the optimal estimation are given. Features of tested equipment are described. The quadrotor trajectory in the horizontal plane is simulated. Coordinates of the topocentric reference frame are researched. The results of the experimental test are shown. The components of velocity are represented. The graphical dependences on the yaw, pitch, and roll are shown. The obtained results can be useful for creating perspective navigation systems for quadrotors. They allow to improve the quality of quadrotor navigation.

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Section: Introduction and Problem Statementmentioning

confidence: 99%

Experimental Research of Integrated Navigation Systems in Problems of Quadrotor Path Tracking

Kondratiuk

Ilnytska

Kutsenko

et al. 2022

ECS

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“…Autonomous navigation in environments without prior knowledge is a crucial problem for various autonomous vehicles [ 1 , 2 , 3 ]. The inertial navigation system, also known as INS, had been widely used to provide position estimates.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Localization and Mapping with Iterative Sparse Extended Information Filter for Autonomous Vehicles

Liu

Dong

Shen

et al. 2015

Sensors

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In this paper, a novel iterative sparse extended information filter (ISEIF) was proposed to solve the simultaneous localization and mapping problem (SLAM), which is very crucial for autonomous vehicles. The proposed algorithm solves the measurement update equations with iterative methods adaptively to reduce linearization errors. With the scalability advantage being kept, the consistency and accuracy of SEIF is improved. Simulations and practical experiments were carried out with both a land car benchmark and an autonomous underwater vehicle. Comparisons between iterative SEIF (ISEIF), standard EKF and SEIF are presented. All of the results convincingly show that ISEIF yields more consistent and accurate estimates compared to SEIF and preserves the scalability advantage over EKF, as well.

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Unmanned aerial vehicle position determination in GNSS landing system

Kutsenko

Ilnytska

Kondratyuk

et al. 2017

2017 IEEE 4th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD)

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Urgent problems of UAV navigation system development and practical implementation

Cited by 13 publications

References 5 publications

Experimental Research of Integrated Navigation Systems in Problems of Quadrotor Path Tracking

Experimental Research of Integrated Navigation Systems in Problems of Quadrotor Path Tracking

Simultaneous Localization and Mapping with Iterative Sparse Extended Information Filter for Autonomous Vehicles

Unmanned aerial vehicle position determination in GNSS landing system

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