Unmanned Aerial Vehicles Formation Research Articles

A Leader-Follower Trajectory Tracking Controller for Multi-Quadrotor Formation Flight

The aim of this work is to design a control system based on modern control methods to control flight formations of quadrotor unmanned aerial vehicles. A leader-follower methodology is implemented where the leader vehicle has some predefined trajectory, and the follower vehicles are controlled in order to track the leader while keeping a constant displacement. The formation control system, responsible for the vehicle formation, considers, at first, only the motion at a constant height, and secondly, the three-dimensional motion. In both cases, the nonlinear control laws are derived based on Lyapunov stability theory and the Backstepping method. The control laws are validated in simulation, resorting to a realistic environment and vehicle models.

Configuration Transformation Planning Method of Unmanned Aerial Vehicle Cluster Based on Improved Hungarian Algorithm

For the planning problem of Unmanned Aerial Vehicle (UAV) formation configuration transformation, a formation configuration transformation planning method based on the improved Hungarian algorithm is proposed. By selecting a straight-line path as the movement path of UAVs in configuration transformation, the configuration transformation problem is transformed into a multi-UAV position assignment problem with constraint handling in a dynamic environment. For the Hungarian algorithm efficiency matrix power function treatment, the improved algorithm can be simultaneously bivariate integrated optimization; Introduce the time axis in the configuration space to establish the configuration-time space, and analyze the collision constraints during the dynamic transformation process in this space, and finally, the feasibility of the method is verified by simulation.

Flight Test of Autonomous Formation Management for Multiple Fixed-Wing UAVs Based on Missile Parallel Method

This paper reports on the formation and transformation of multiple fixed-wing unmanned aerial vehicles (UAVs) in three-dimensional space. A cooperative guidance law based on the classic missile-type parallel-approach method is designed for the multi-UAV formation control problem. Additionally, formation transformation strategies for multi-UAV autonomous assembly, disbandment, and special circumstances are formed, effective for managing and controlling the formation. When formulating the management strategy for formation establishment, its process is divided into three steps: (i) selecting and allocating target points, (ii) forming loose formations, and (iii) forming short-range formations. The management of disbanding the formation is formulated through reverse thinking: the assembly process is split and recombined in reverse, and a formation disbanding strategy that can achieve a smooth transition from close to lose formation is proposed. Additionally, a strategy is given for adjusting the formation transformation in special cases, and the formation adjustment is completed using the adjacency matrix. Finally, a hardware-in-the-loop simulation and measured flight verification using a simulator show the practicality of the guidance law in meeting the control requirements of UAV formation flight for specific flight tasks.

Optimal path selection algorithm for UAV formation guided by a UV virtual fence.

This paper studies the optimal flight path selection problem of unmanned aerial vehicle (UAV) formations in multi-obstacle areas. According to the characteristics of wireless ultraviolet (UV) light communication conforming to the probability coverage model, a wireless UV light self-organizing network coverage model is proposed; the UV light of different wavelengths is divided into a detection area, communication area, and early warning area. A consensus algorithm with leaders and followers is designed, and an artificial potential field method is introduced to ensure that the UAV formation successfully avoids obstacles. Simulation results show that the UAV formation can choose a reasonable flight route under the improved algorithm, and the average obstacle avoidance time is reduced by 6.75 s compared with the original algorithm. Comparing the flight paths of formations in barrier-free and multi-obstacle environments, the obstacle avoidance range of UAVs is not more than 1 m. The UV light self-organizing coverage model can be applied to military communications and disaster relief.

Formation control of unmanned aerial vehicle swarms: A comprehensive review

AbstractThe unmanned aerial vehicle formation plays a crucial role in numerous applications, such as reconnaissance, agricultural plant protection, and electric power inspection. This paper provides a comprehensive review and analysis of the unmanned aerial vehicle swarm communication networks and formation control strategies. First, the most commonly used unmanned aerial vehicles are introduced and compared. Next, the entire process of the formation task, from the formation assignment to the formation transformation, is detailed described. At last, the widely adopted communication networks are analyzed, and the existing formation control strategies of the UAV swarm are compared, which shows that the distributed formation control is superior to the centralized method and is the future development trend.

Cooperative Obstacle Avoidance for Multiple UAVs Using Spline_VO Method.

In order to solve multiple unmanned aerial vehicle (UAV) dynamic collision avoidance, a cooperative obstacle avoidance algorithm considering UAV’s kinematic constraints has been developed. In the proposed algorithm, the useful information of UAVs is screened out by a Heartbeat information filtering mechanism and fused by the user datagram protocol (UDP) communication method, which improves communication performance among UAVs. In addition, the velocity obstacle (VO) method combined with cubic uniform B-spline curve is used to avoid obstacles and generate smooth paths, which can be applied to practical scenes. Finally, dynamic and static obstacle avoidance simulations are carried out to verify the effectiveness of the proposed algorithm.

A Distributed Control for Ground Target Tracking of Nonlinear Unmanned Aerial Vehicles Formation

This paper investigates a circular formation control strategy for multiple unmanned aerial vehicles (multi-UAV) formation for ground moving target tracking. Each UAV obtains the observation value of target information through sensors and exchanges data with its neighbors. Since the formation cannot get the parameter of the target directly, we proposed a distributed error observer. A new guidance law based on the error value obtained has been designed, and it was proved through the interconnection system that it was consistent with Lyapunov stability. Finally, a simulation example is used to illustrate the effectiveness of the proposed guidance law.

Cooperative navigation for UAVs in GNSS-denied area based on optimized belief propagation

A multitude of individual unmanned aerial vehicle (UAV) cooperatively self-organized as a swarm attracts increasing attention for exploration and parallel tasks. Accurate position is essential for UAVs to avoid collision and implement control. Although the Global Navigation Satellite System (GNSS) has been integrated in UAV, it is susceptible to disruption. In this paper, we propose a novel cooperative navigation framework based on optimized belief propagation (BP) in the GNSS-denied area. Specifically, we derive a directional uncertainty model to characterize the position information of UAVs with different dynamic motions. With this model, we improve the navigation performance by designing a weighted uncertainty belief propagation (WUBP) based on information evaluation. Simulation and experimental results validate that in the dynamic scenarios, the proposed WUBP can make the swarm reap the benefits of more accurate positional estimate from UAVs with less maneuvers, higher-grade of INS or shorter time interval of GNSS signal lost.

Adaptation to Unknown Leader Velocity in Vector-Field UAV Formation

This article presents a new adaptive method for formation control of unmanned aerial vehicles (UAVs) with limited leader information and communication. We study a formation control protocol in the framework of vector-field guidance where the leader can communicate its position and orientation but not its velocity. A practical motivation for this scenario is the so-called congestion-aware control, in which tradeoffs between the density of unmanned vehicles and communication interference caused by many communicating vehicles arise: these tradeoffs may require to reduce the communication load to avoid interference. To compensate for the lack of knowledge of the leader velocity, each UAV makes use of a local estimation mechanism. The resulting method is an adaptive control method, whose stability can be established using Lyapunov stability. We show that the method can be extended to a distributed communication setting with a few neighboring UAVs in place of the leader. Extensive simulations with different formation shapes (Y, V, and T formation) show that the proposed adaptation mechanism effectively achieves the formation despite the unknown leader velocity. The proposed mechanism has a very similar performance to the ideal case when the leader velocity is perfectly known, and outperforms all the nonadaptive cases in which the followers have an incorrect knowledge of the leader velocity.

UAV-Based Physical-Layer Intelligent Technologies for 5G-Enabled Internet of Things: A Survey

In recent years, the utilization and application of unmanned aerial vehicle (UAV) have attracted much attention, both from academy and industry. UAVs have been widely used in many practical communication scenarios, due to its high flexibility, high mobility, and low cost. Therefore, this paper addresses the key technologies of UAV communication and reviews the current research status, from various aspects including UAV communication transmission, UAV formation control and networking, UAV resource allocation, and intelligent communication from artificial intelligence algorithms. Then, artificial intelligence is introduced into multiple aspects of UAV communication, including channel transmission, control and networking, and resource scheduling, to organically integrate artificial intelligence into UAV communication, which can help reduce the complexity of communication algorithms and improve system spectrum efficiency. This paper will help improve the efficiency of UAV communication and promote the development of UAV-related industries.

Analysis and Research of multi-UAV autonomous formation based on azimuth adjustment model

The slight deviation of some plane positions of the Unmanned Aerial Vehicle (UAV) cluster in the formation flight is caused by force majeure factors. To maintain the UAV formation, the silent mode is defined, that is, the UAV thin line flight. The circular formation model and the UAV bearing adjustment model of the conical cluster UAV positioning are established. The UAV position can be adjusted, and the UAV formation can be adjusted into a circular formation and a conical formation.

Decentralized Multi-UAV Path Planning Based on Two-Layer Coordinative Framework for Formation Rendezvous

Unmanned aerial vehicle (UAV) formation rendezvous path planning problem is one of the important research topics in multiple UAV (multi-UAV) coordinated path planning. Aiming at solving low computational efficiency and poor scalability of the traditional multi-UAV path planning method, the decentralized multi-UAV path planning method suitable for obstacle environments is proposed. Firstly, the UAV rendezvous path planning problem with constraints such as the kinematics of UAVs and collision-free constraints is modeled as a non-convex optimal-control problem. To minimize formation rendezvous time and energy consumption, a two-layer coordinative framework is developed to solve this problem. In the coordination layer, relying only on the information of neighboring UAVs, each UAV in the decentralized communication graph negotiates the desired flight time using a consensus protocol to achieve coordination among UAVs. In the planning layer, the initial non-convex formation rendezvous path planning problem is decoupled into several sub-problems, which can be solved in parallel by path planners distributed on each UAV using sequential convex programming. Finally, numerical simulations are carried out to verify the effectiveness and scalability of the proposed method. The results show that this decentralized multi-UAV path planning method can handle the minimum-time rendezvous path planning problem and optimize the energy consumption in flight, and the computing time does not increase significantly with the enlargement of the UAV swarm. This decentralized framework scales well with the number of UAVs and can be applied for future urban flight and supplies delivery tasks.

Neighbour Discovery Algorithm for Wireless Cooperative Unmanned Aerial Vehicle Formation

Neighbour Discovery Algorithm for Wireless Cooperative Unmanned Aerial Vehicle Formation

Clustering Optimization Algorithm for Unmanned Aerial Vehicle Formation Based on Ultraviolet Security Communication

Clustering Optimization Algorithm for Unmanned Aerial Vehicle Formation Based on Ultraviolet Security Communication

Event-triggered prescribed settling time consensus control of uncertain nonlinear multiagent systems with given transient performance

Multiagent systems (MASs) are usually used in unmanned aerial vehicle formations, multi-manipulator coordinated, traffic vehicle control and other fields, which have attracted a lot of attention from scholars. In this research, with the help of the designed performance function, the nonlinear transformation of synchronization error is realized. And the synchronization error of MASs with given transient performance could converge to the predefined interval. According to the designed transformation function, a prescribed setting time consensus control is investigated with the advantages of Radial Basis Function Neural Networks (RBFNNs) in dealing with unknown functions. It guarantees that the MASs under consideration are uniformly bounded convergent. Furthermore, event-triggered mechanism is applied to relieve pressure of MASs’ communication resources. Simulation results demonstrate its effectiveness.

Performance Analysis and Optimization of a UAV-Enabled Two-Way Relaying Network Under FSMH, NC, and PNC Schemes

Unmanned aerial vehicles (UAVs) have played an important role in wireless communications due to the advantages, such as highly controllable mobility in 3-D space, swift deployment, Line-of-Sight (LoS) aerial–ground links, and so on. In this article, we consider a UAV-enabled two-way relaying system, where the UAV relay assists the information exchange between two ground users (GUs) under three different schemes, i.e., four-slot multihopping (FSMH) without network coding (NC), three-slot NC, and two-slot physical NC (PNC). First, the capacity region of each scheme in this relaying system is analyzed. Then, we maximize the system average sum rate by jointly optimizing the time resource allocation, transmission powers of the transceivers, and the UAV trajectory subject to the constraints on UAV mobility and information causality under each scheme. To solve those problems, we propose an iterative algorithm by applying the successive convex approximation and block coordinate descent techniques. Specifically, the time resource allocation, transmission powers, and the UAV trajectory are alternatively optimized in each iteration. In addition, the nonconvex trajectory optimization problem is solved by successively solving an approximate convex optimization problem. To gain more insights, we also investigate the performance of those three schemes with symmetric and asymmetric traffic, respectively, by introducing a new traffic pattern constraint. Numerical results show that the proposed relaying schemes with moving relay can achieve great throughput gains as compared to the conventional scheme with static relay. The three relay schemes also show great performance heterogeneity under different traffic patterns.

Simulation and Analysis of Grid Formation Method for UAV Clusters Based on the 3 × 3 Magic Square and the Chain Rules of Visual Reference

Large-scale unmanned aerial vehicle (UAV) formations are vulnerable to disintegration under electromagnetic interference and fire attacks. To address this issue, this work proposed a distributed formation method of UAVs based on the 3 × 3 magic square and the chain rules of visual reference. Enlightened by the biomimetic idea of the plane formation of starling flocks, this method adopts the technical means of airborne vision and a cooperative target. The topological structure of the formation’s visual reference network showed high static stability under the measurement of the network connectivity index. In addition, the dynamic self-healing ability of this network was analyzed. Finally, a simulation of a battlefield using matlab showed that, when the loss of UAVs reaches 85% for formations with different scales, the UAVs breaking formation account for 5.1–6% of the total in the corresponding scale, and those keeping formation account for 54.4–65.7% of the total undestroyed fleets. The formation method designed in this paper can maintain the maximum number of UAVs in formation on the battlefield.

Multi UAV Coverage Path Planning in Urban Environments.

Coverage path planning (CPP) is a field of study which objective is to find a path that covers every point of a certain area of interest. Recently, the use of Unmanned Aerial Vehicles (UAVs) has become more proficient in various applications such as surveillance, terrain coverage, mapping, natural disaster tracking, transport, and others. The aim of this paper is to design efficient coverage path planning collision-avoidance capable algorithms for single or multi UAV systems in cluttered urban environments. Two algorithms are developed and explored: one of them plans paths to cover a target zone delimited by a given perimeter with predefined coverage height and bandwidth, using a boustrophedon flight pattern, while the other proposed algorithm follows a set of predefined viewpoints, calculating a smooth path that ensures that the UAVs pass over the objectives. Both algorithms have been developed for a scalable number of UAVs, which fly in a triangular deformable leader-follower formation with the leader at its front. In the case of an even number of UAVs, there is no leader at the front of the formation and a virtual leader is used to plan the paths of the followers. The presented algorithms also have collision avoidance capabilities, powered by the Fast Marching Square algorithm. These algorithms are tested in various simulated urban and cluttered environments, and they prove capable of providing safe and smooth paths for the UAV formation in urban environments.

Model decomposition-based optimal formation control for multiple unmanned aerial vehicles

This paper deals with the optimal formation control problem based on model decomposition for multiple unmanned aerial vehicles (UAVs). The main contribution of this paper is to integrate the formation control and the trajectory tracking into one unified feedforward control and feedback control framework in an optimal mode. We first establish the dynamic model of the leader-follower UAV formation system, and the communication network topology which only depends on the position information given by the leader. Second, to reduce the complexity of the model, each follower is decomposed into three isolated subsystems. Third, a step-by-step formation controller design scheme decomposed into feedforward control and optimal control of formation control is proposed. Finally, the proposed scheme has been extensively simulated and the results demonstrate the stability and the optimality.

Disturbance observer-based backstepping formation control of multiple quadrotors with asymmetric output error constraints

This paper presents a distributed formation tracking control strategy which acts on multiple quadrotor unmanned aerial vehicles (QUAVs) formation control under external disturbance and asymmetric output error constraints. An asymmetric barrier Lyapunov function (BLF) is applied to ensure the constraint of output error. Based on graph theory and backstepping control method, a distributed formation controller is designed to achieve the formation and maintenance of formations, where external disturbance is handled by disturbance observer (DO). In the framework of Lyapunov theory, the bounded stability of the closed-loop system is proved, and the output error is remained within the constraint range. The superiority and effectiveness of the designed control strategy is verified by the compared simulation.