Distributed unmanned aerial vehicles formation with built-in safety systems

Introduction Autonomous unmanned aerial vehicles (UAVs) are considered with increasing interest in a diverse set of civil and commercial applications, such as environmental and natural disaster monitoring, border surveillance, emergency assistance, search and rescue missions, delivery of goods, and construction [208, 132, 362, 265, 434, 110, 280, 163]. Use of single or multiple UAVs as communication relays or aerial base stations for network provisioning in emergency situations and for public safety communications has been of particular interest due to UAVs fast deployment and large coverage capabilities [331, 193, 206, 429]. The deployed aerial platform size and the number of necessary platforms are key factors in determining the on-board communication system in addition to the coverage and capacity requirements [73]. Small-scale multi-rotors are of particular interest in practice due to their ease of deployment, low acquisition and maintenance costs, high maneuverability, and ability to hover. Research and development of small-scale UAVs focused initially on control issues, such as flight stability, maneuverability, and robustness, followed by designing autonomous vehicles capable of waypoint flights with minimal user intervention. Considering the limited flight time and payload capacity of these vehicles and the area sizes the aforementioned applications might span, the interest is shifting more and more toward collaborative multiple UAV systems for efficient and successful missions. The number of UAVs might be from tens to hundreds traveling over tens of meters to kilometers for different applications (see Figure 3.1 for an illustration). Wireless communication is an essential factor not only for network provisioning with UAVs but also for successful deployment of systems consisting of multiple small-scale UAVs. It is highly likely that high-performance links and connectivity in three-dimensional space will be required for several applications (e.g., monitoring certain areas) with data delivery meeting a certain quality of service demands [35].The question arises as to which wireless technology should be employed for aerial networks that consist of air-to-ground and air-to-air links, and data needs to be delivered regardless of significant height and orientation differences. Taking into account the quality of service to be satisfied over diverse links and the high node mobility, it is not yet clear as to whether networking protocols developed for ground networks are readily deployable on UAV networks.

In this article simultaneous arrival of multiple unmanned aerial vehicle (UAV) at a common point was studied in a fixed network hierarchy is used. By considering the model of fixed wing UAV the decentralized based control algorithm is developed for the formation control of all UAV’s. The tree based networked geometry is developed for the formation control of multiple UAV’s with respect to the leader. Whereas, UAV’s agent or (leader / follower) are autonomously connected with each other. Formation of flight via decentralized control structure which contains two parts, one is to achieve the arrival of expected meet-point for the formation geometry and other is to maintain the synchronization of all UAV’s. Moreover, the leader is supposed and able to regulate the speed or velocity of UAV’s. Simulated results showed that arrival of multiple UAV’s at a common point for the formation is achieved successfully and the above designed control algorithm has good robustness and flexible.

This paper considers the problem of cooperative target tracking with multiple unmanned aerial vehicles (UAVs) subject to input constraints. Cooperation of multiple UAVs to track a moving target can provide better performance and enhance the robustness. However, the physical constraints of the UAVs pose a significant challenge on the UAV controller design. In this paper, the relative course rate controller for a single UAV is firstly developed based on a guidance vector field. Cooperative control strategy of multiple UAVs is studied and a variable airspeed controller is proposed to regulate temporal separation of UAVs. Simulation results are provided to demonstrate the effectiveness of the proposed approach.

Hybrid modeling and control issues provide a flexible powerful tool for Unmanned Aerial Vehicles (UAVs) as complex control platforms. This paper aims to briefly review recent results in this area. Firstly, existing works on hybrid modeling and control of a single UAV are reviewed. Then multiple UAVs control in a synchronously cooperative task planning, which gives much more maneuverability, has been surveyed in the hybrid framework. Formation control of UAVs is a typical cooperative strategy with considerable applications in multi-agent aerial robotics area and can leverage limited abilities of single UAVs into complicated tasks of group missions. There are a few works in this field which we briefly reviewed their results and explored the possible future directions of these research activities.

To archive diverse kinds of goal, multiple unmanned aerial vehicles (UAVs) need to cooperate each other. Therefore, the importance of a ground station becomes more important. This paper proposes a framework of the ground station that controls multiple and hetero UAVs. The framework contains multiple UAV control modules and UI interfaces and has the flexibility for adding diverse kinds of UAVs and embedded devices such as commercial UAVs, Arduino-based UAVs, cameras and storage devices.

We present a distributed control strategy for a team of fixed-wing Unmanned Aerial Vehicles (UAVs), such that they achieve a desired formation and travel along a desired direction at a constant altitude. We describe the motion of UAVs with the kinematic unicycle model, and impose the constraints that the airspeed and turning rate of UAVs must satisfy some practical bounds. Based on this model, a control strategy is proposed, and local convergence of the team to the desired formation and travel direction is proved. The control direction returned by our strategy is well-suited as a high-level motion planning input to a low-level UAV autopilot, which can compensate for the aerodynamics, wind effects, disturbances, etc., that are not accounted for in the unicycle model. The proposed strategy is fully distributed and can be implemented using relative position measurements acquired by UAVs in their local coordinate frames. Furthermore, UAVs do not need to communicate. Simulations are provided to typify the proposed strategy.

Distributed formation control of multi-UAV systems using relative information

Unmanned Aerial Vehicles (UAVs) have been widely used in various applications such as inspection, security surveillance, and aerial photography, in which the cooperation of multiple UAVs is significantly important for better accomplishing complex tasks due to the limited capability for individual UAV s. Task planning is the primary issue for the cooperation of multiple UAV s, and has attracted extensive research interests. However, most research fails to account adequately for limited energy on each UAV, which involves in many factors such as different operations for performing a task and various movement patterns besides the distance and turns that have been commonly considered. By contrast, we conduct a series of experiments to obtain the energy model of UAV s. Furthermore, we focus on the energy-efficient min-max task planning (E2M2TP) problem by considering the heterogeneity of tasks and integrating various energy factors, which is beneficial for balancing the workload and energy consumption among UAV s and thus reducing the number of required UAVs. We show that E2M2TP is NP-hard, and propose an energy-aware variable neighbor search (EVNS) algorithm to iteratively optimize both task allocation and path planning. Extensive simulations are conducted to validate that EVNS outperforms the other state-of-the-art algorithms.

Distributed formation control for multiple quadrotor UAVs under Markovian switching topologies with partially unknown transition rates

In this paper, we present a distributed control architecture for multiple Unmanned Aerial Vehicles (UAVs) to search, detect, and monitor emergency sites using camera sensors. The motivation for our current work is to meet the Air Force’s needs to quickly search and detect emergency sites, providing necessary aerial support to ground forces. The control architecture is designed for multiple independent UAVs with limited communication range. Each UAV makes decisions independently based on its sensor information and information it receives from other UAVs in its vicinity. We demonstrate the validity of our control architecture using results obtained from a graphical simulator developed in-house. In addition, we show Piccolo c flight control system simulation results, the first step toward implementing the control architecture onto a hardware unmanned aircraft system. The simulation on the graphical simulator is performed with multiple UAVs and multiple emergency sites, while the hardware simulation is done using two autonomously controlled aircraft and one emergency site.

In the broad class of unmanned aerial vehicles (UAV), Quadrotor is an important member. Cooperative control of UAVs are currently being researched for a wide range of applications. An active and important research area of cooperative control of multiple UAVs is the formation control. Formation flying is the disciplined flight of two or more aircraft under the command of a flight leader. The main goal is to coordinate a group of UAVs to achieve a desired formation pattern and avoid inter-vehicle collisions at the same time. Formation flight of a team of UAVs has broad applications such as aerial mapping, traffic monitoring, terrain and utilities inspection, search and rescue operations, perimeter planning, disaster monitoring, reconnaissance mission, surveillance etc. Here we propose a Line Of Sight (LOS) guidance based flight formation control strategy for multiple quad rotor UAVs in leader-follower framework. The guidance laws for 2D formation are implemented with the help of LOS angles, between adjacent quadrotors to keep the current quadrotor's position in formation. The full dynamic model of quadrotor incorporating LOS guidance law is considered for designing PID controller and the simulation analysis was done using MATLAB/ Simulink.

As a quite interesting subject, there are an increasing number of researches about UAV (Unmanned Aerial Vehicle) in the literature.These robots are quite suitable to dull, dirty and dangerous missions (e.g., over flights at low altitude, especially at night, and longrunning operations, which exposes the crew to extreme fatigue).Thus, an important application of these vehicles is the search operations involving multiple UAVs.However, despite the huge potential use of the UAVs, cooperative search operations with this kind of flying robots are not yet occurring.This research topic is a multidisciplinary area of study in its beginning.Several issues can be studied related to cooperative UAV for search operations, such as centralized versus decentralized control, path planning for cooperative flies, agent reasoning for UAV tactical planning, safety assessments, reliability in automatic target reconnaissance by cameras, agent coordination mechanisms applied for UAV cooperation and the application itself (e.g., patrolling, remote sensing, search and rescue operations supporting, etc.).This paper proposes a model that combines path planning algorithms, search patterns and multiagent coordination techniques to obtain a cooperative UAV model.Different path planning algorithms were studied aiming to get the most suitable to these kinds of operations, and the conclusions are presented.In addition, official documents of Search and Rescue operations are also studied in order to know the best practices already established for this kind of operations, and, finally, an overview of the coordination multi-agent theory is presented and evaluated to achieve the UAV coordination.The great goal for cooperative UAV is to achieve such performance that the performance of the group overcomes the sum of the individual performances isolatedly.Comparing two cooperative UAVs with two non-cooperative UAVs, simulations of previous work showed an average increase in efficiency by about 100%.Besides, another aspect was simulated and evaluated: the impact of the density of the initial sweep.The computational simulations show a high potential of reducing even more the time of search.Furthermore, it is worth noting that the usefulness of cooperative UAVs is not only the increase in efficiency, but also the reduction of costs and risks for the crew.

This thesis focuses on the use of multiple unmanned aerial vehicles(UAVs) in a distributed framework to synchronously perform shared tasks. These include aerial beamforming and coordinated mapping. It also focuses on use of multiple UAVs with the overall goal of enhancing the reliability of performing periodic (mapping) tasks at remote locations for long-term autonomous(LTA) missions. In the first part of the thesis, we focus on hardware architecture for UAVs to enable reliable LTA missions with minimal human intervention. We developed a Size, Weight, and Power(SWaP) constrained smart charging stack to minimize hotel loads seen during the recharging process and enable efficient charging of batteries. This leads to the design of a standalone, solar rechargeable quadcopter. Real-world applications such as reconstructing a dynamic scene from multiple viewpoints and distributed aerial beamforming require multiple robots(agents) to coordinate and synchronously act to accomplish shared tasks. These tasks require spatially distant, multiple UAVs to have time, phase, and frequency synchronization. We demonstrate a Synchronous UAV(S-UAV) architecture for wireless synchronization based on GPS disciplined oscillators and the associated software framework needed for temporal registration of data across multiple UAVs. We have built four S-UAVs and demonstrate the ability to 3D reconstruct a dynamic scene from overlapping viewpoints. Dynamic baseline camera arrays formed using multiple S-UAVs are used to synchronously capture a dynamic environment with people moving around. A single-time instance of synchronously captured images of the scene is used to 3D reconstruct the dynamic environment while preserving static scene assumptions of Structure from Motion(SFM). In the second part of the thesis, we focus on a multi UAV autonomy framework for real-world applications of UAVs in perception, wireless communications, and reliable LTA missions. We present 'Simplenav,' a navigation stack for heterogeneous, multiple UAVs. We demonstrate this framework with novel applications of end-to-end autonomy pipelines developed for a coordinated swarm of UAVs.--Author's abstract

Today, the use of small unmanned aerial vehicles (UAVs) has increased due to technological advances. There has been an interest in using multiple UAVs instead of a single UAV to accomplish a given mission. This is because there are many scenarios where the capabilities of a single UAV are inadequate due to certain constraints (battery capacity, time in the air). For this reason, swarm UAV studies have increased. A swarm UAV consists of a large number of UAVs cooperating to accomplish a specific mission. This study shows three-dimensional formation control of a swarm UAV system in an obstacle environment. A centralized control architecture is used in this process. All task assignments are made from a centralized system. The Artificial potential fields method creates the formation at the target point by avoiding obstacles. The study was carried out using the Robot Operating System (ROS). The methods were tested in Webots simulation environment. Crazyflie robots were used in the experiments. In the simulation environment, square, star and v formations were first tested in two dimensions. Then, as an example of three-dimensional formation, the cubic and pyramid formations were created and observed.

The development of hierarchical structures of unmanned aerial vehicles (UAVs) increases the efficiency of unmanned aerial systems. The grouping of UAVs increases the region of recognition or force of assault. Achieving these requirements is possible through a UAV formation. The UAVs in the formation must be controlled and managed by a commander, but the commander cannot control individual UAVs. The UAVs within the formation have assigned specific individual tasks, so is possible to achieve the flight of the formation with minimum collisions between UAVs and maximized equipment utilization. This paper aims to present a method of formation control for multiple UAVs that allows dynamic changes in the constellations of UAVs. The article includes the results of tests and research conducted in real-world conditions involving a formation capable of adapting its configuration. The results are presented as an element of research for the autonomy swarm, which can be controlled by one pilot/operator. The control of a swarm consisting of many UAVs (several hundred) by one person is now a current problem. The article presents a fragment of research work on high-autonomy UAV swarms. Here is presented a field test that focuses on UAV constellation control.