A Semi-Physical Platform for Guidance and Formations of Fixed-Wing Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) have multi-domain applications, fixed-wing UAVs being a widely used class. Despite the ongoing research on the topics of guidance and formation control of fixed-wing UAVs, little progress is known on implementation of semi-physical validation platforms (software-in-the-loop or hardware-in-the-loop) for such complex autonomous systems. A semi-physical simulation platform should capture not only the physical aspects of UAV dynamics, but also the cybernetics aspects such as the autopilot and the communication layers connecting the different components. Such a cyber-physical integration would allow validation of guidance and formation control algorithms in the presence of uncertainties, unmodelled dynamics, low-level control loops, communication protocols and unreliable communication: These aspects are often neglected in the design of guidance and formation control laws for fixed-wing UAVs. This paper describes the development of a semi-physical platform for multi-fixed wing UAVs where all the aforementioned points are carefully integrated. The environment adopts Raspberry Pi’s programmed in C++, which can be interfaced to standard autopilots (PX4) as a companion computer. Simulations are done in a distributed setting with a server program designed for the purpose of routing data between nodes, handling the user inputs and configurations of the UAVs. Gazebo-ROS is used as a 3D visualization tool.

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Optimizing Perimeter Surveillance Drones to enhance the security system of unmanned aerial vehicles

Security science journal ◽

10.37458/ssj.2.2.7 ◽

2021 ◽

Vol 2 (2) ◽

pp. 105-115

Author(s):

Mahmod Al-Bkree

Keyword(s):

Unmanned Aerial Vehicles ◽

Security System ◽

Small Scale ◽

Security Systems ◽

Ongoing Research ◽

Aerial Vehicles ◽

Aerial Vehicle ◽

Initial Results

This work is to optimize perimeter surveillance and explore the distribution of ground bases for unmanned aerial vehicles along the Jordanian border and optimize the set of technologies for each aerial vehicle. This model is part of ongoing research on perimeter security systems based on unmanned aerial vehicles. The suggested models give an initial insight about selecting technologies carried by unmanned aerial vehicles based on their priority; it runs for a small scale system that can be expanded, the initial results show the need for at least four ground bases along the length of the border, and a selected set of various technologies for each vehicle.

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Bird Flocking Inspired Formation Control for Unmanned Aerial Vehicles Using Stereo Camera

IEEE Systems Journal ◽

10.1109/jsyst.2018.2884051 ◽

2019 ◽

Vol 13 (3) ◽

pp. 3580-3589 ◽

Cited By ~ 3

Author(s):

Jonathan Lwowski ◽

Abhijit Majumdar ◽

Patrick Benavidez ◽

John J. Prevost ◽

Mo Jamshidi

Keyword(s):

Unmanned Aerial Vehicles ◽

Formation Control ◽

Stereo Camera ◽

Aerial Vehicles

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Design and flight-stability analysis of a closed fixed-wing unmanned aerial vehicle formation controller

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1177/0959651818821448 ◽

2018 ◽

Vol 233 (8) ◽

pp. 1045-1054 ◽

Cited By ~ 2

Author(s):

Jialong Zhang ◽

Bing Xiao ◽

Maolong Lv ◽

Qiang Zhang

Keyword(s):

Unmanned Aerial Vehicles ◽

Collision Avoidance ◽

High Speed ◽

Physical Simulation ◽

Controller Design ◽

Formation Flight ◽

External Factors ◽

Flight Stability ◽

Aerial Vehicles ◽

Closed Formation

This article addresses a flight-stability problem for the multiple unmanned aerial vehicles cooperative formation flight in the process of the closed and high-speed flight. The main objective is to design a cooperative formation controller with known external factors, and this controller can keep the consensus of attitude and position and reduce the communication delay between any two unmanned aerial vehicles and increase unmanned aerial vehicles formation cruise time under the known external factors. Known external factors are taken into consideration, and longitude maneuvers using nonlinear thrust vectors were employed with unsteady aerodynamic models, according to the attitude and position of unmanned aerial vehicles, which were employed as corresponding input signals for studying the dynamic characteristics of unmanned aerial vehicles formation flight. In addition, the relative distance between any two unmanned aerial vehicles was not allowed to exceed their safe distance so that the controller could perform collision avoidance. An analysis of formation flight distance error shows that it converged to a fixed value that well ensured unmanned aerial vehicles formation flight stability. The experimental results show that the controller can improve the speed of a closed formation effectively and maintain the stability of formation flight, which provides a method for closed formation flight controller design and collision avoidance for any two unmanned aerial vehicles. Meanwhile, the effectiveness of proposed controller is fully proved by semi-physical simulation platform.

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Lyapunov vector-based formation tracking control for unmanned aerial vehicles with obstacle/collision avoidance

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331219879338 ◽

2019 ◽

Vol 42 (5) ◽

pp. 942-950

Author(s):

Kai Chang ◽

Dailiang Ma ◽

Xingbin Han ◽

Ning Liu ◽

Pengpeng Zhao

Keyword(s):

Unmanned Aerial Vehicles ◽

Potential Field ◽

Formation Control ◽

Control Method ◽

Spherical Surface ◽

Moving Target ◽

Local Optima ◽

Formation Tracking ◽

Aerial Vehicles ◽

Repulsive Forces

This paper presents a formation control method to solve the moving target tracking problem for a swarm of unmanned aerial vehicles (UAVs). The formation is achieved by the artificial potential field with both attractive and repulsive forces, and each UAV in the swarm will be driven into a leader-centered spherical surface. The leader is controlled by the attractive force by the moving target, while the Lyapunov vectors drive the leader UAV to a fly-around circle of the target. Furthermore, the rotational vector-based potential field is applied to achieve the obstacle avoidance of UAVs with smooth trajectories and avoid the local optima problem. The efficiency of the developed control scheme is verified by numerical simulations in four scenarios.

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