Increasing the reliability of drones due to the use of quaternions in motion

Kritskiy, Dmitriy; Alexander, Karatanov; Koba, Serhii; Дружинин, Е. И.

doi:10.1109/dessert.2018.8409157

Cited by 11 publications

(4 citation statements)

References 7 publications

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“…Many studies, including those by Waymo engineers, consider the use of machine learning to solve autopilot control tasks. For example, they use neural networks to analyse the traffic situation and make driving decisions [1][2][3][4].…”

Section: Analysis Of the Latest Research And Publicationsmentioning

confidence: 99%

Section: Performing Research 1 Development Of Control Laws For the Fl...mentioning

confidence: 99%

“…However, it is difficult to take into account the saturation of actuators in this approach and it is difficult to include state constraints. In addition, such autopilots, especially for UAV flight with high flight dynamics, are very sensitive to errors and simplifications in mathematical models[3].By modifying the interaction architecture, a heterogeneous method can be described that is proposed both in terms of the magnitude and direction of the path vector field.To control single UAVs, the paper proposes the method of the path following vector field. A similar method is called the Lyapunov vector field method.…”

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confidence: 99%

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Development of Control Laws of Unmanned Aerial Vehicles for Performing Group Flight at the Straight-Line Horizontal Flight Stage

Barabash,

Kyrianov

2023

A.I.S.

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The article proposes an improved approach to controlling groups of unmanned aerial vehicles (UAVs) aimed at increasing the overall efficiency and flexibility of the control process. The use of a heterogeneous external field, which varies both in magnitude and direction, allows achieving greater adaptability and accuracy in controlling a group of UAVs. A vector field for unmanned aerial vehicles determines the direction and intensity of the vehicles' movement in space. Such vector fields can be used to develop UAV control laws, including determining optimal flight paths, controlling speed, avoiding obstacles, and ensuring coordination of a group of UAVs. The subject of the study is the methods of controlling groups of autonomous UAVs, where each vehicle may have different speeds and flight directions. To solve this problem, various methods of using a heterogeneous field have been developed and proposed. Instead of using a homogeneous field that provides a constant flight speed, a vector field is used that adapts to different conditions and characteristics of the vehicles in the group. This method allows for effective group management, ensuring the necessary coordination and interaction between the vehicles. An analysis of recent research and publications in the field of autonomous system control indicates the feasibility of using machine learning, vector fields, and a large amount of data to successfully coordinate the movement of autonomous systems. These approaches make it possible to create efficient and reliable control systems. The aim of the study is to develop laws for controlling the movement of a group of autonomous unmanned aerial vehicles at the stage of straight-line horizontal flight based on natural analogues to improve the efficiency and reliability of their coordinated movement in different conditions. The main conclusions of the research are that the proposed method of controlling groups of UAVs based on a heterogeneous field can be implemented. It takes into account a variety of vehicle characteristics and environmental conditions that are typical for real-world use scenarios. This work opens up prospects for further improving the management of UAV groups and their use in various fields of activity. The article emphasises the relevance of technology development for autonomous unmanned systems, especially in the context of autonomous transport systems.

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Section: Analysis Of the Latest Research And Publicationsmentioning

confidence: 99%

Section: Performing Research 1 Development Of Control Laws For the Fl...mentioning

confidence: 99%

mentioning

confidence: 99%

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Development of Control Laws of Unmanned Aerial Vehicles for Performing Group Flight at the Straight-Line Horizontal Flight Stage

Barabash,

Kyrianov

2023

A.I.S.

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“…Currently, open-source robotics (OSR) platforms have been created for the development of mobile robot control systems, which provide the unified drawings, diagrams, software and infrastructure for implementing the final ideas of third-party developers. Open platforms include RepRap [7,8], FarmBot [9], Yale Open Hand Project [10], e-puck mobile robot [11], Ardumower [12], Hexy [13], OpenROV [14], Pulurobotics [15], Thymio [16], Vorpal the Hexapod [17], Open-source Micro-robotic Project [18], Oscar [19], AnyWalker [20,21], drones such as ArduPilot [22,23], OpenPilot [24], LibrePilot [25], Paparazzi Project [26], Slugs [27], PX4 autopilot [28], humanoid robots such as iCub [29], DARwln-OP [30], InMoov [31], Poppy-project [32], DoraBot [33], NimbRo-OP [34], r-One [35], personal assistants such as Autobed [36], etc.…”

Section: Introductionmentioning

confidence: 99%

Development of a Design Methodology for Cloud Distributed Control Systems of Mobile Robots

Sechenev

Ryadchikov

Gusev

et al. 2021

JSAN

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This article addresses the problem of cloud distributed control systems development for mobile robots. The authors emphasize the lack of a design methodology to guide the process of the development in accordance with specific technical and economic requirements for the robot. On the analysis of various robots architectures, the set of the nine most significant parameters are identified to direct the development stage by stage. Based on those parameters, the design methodology is proposed to build a scalable three-level cloud distributed control system for a robot. The application of the methodology is demonstrated on the example of AnyWalker open source robotics platform. The developed methodology is also applied to two other walking robots illustrated in the article.

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