Multiple Unmanned Aerial Vehicle Systems Research Articles

Distributed Three‐Dimensional Formation Containment Control of Multiple Unmanned Aerial Vehicle Systems

AbstractThis paper concentrates the distributed formation containment problems for multiple unmanned aerial vehicle (UAV) systems under both fixed directed and switching directed topologies. The objective is to introduce the formation control into the containment control research, where master UAVs should exchange information with each other to achieve and maintain a desired formation. Then, two different control protocols are proposed for the master UAVs and slave UAVs, respectively. Utilizing the algebraic graph theory and stability theory, some sufficient conditions are derived to guarantee the master UAVs complete a prespecified formation, while the states of the slave UAVs converge to a convex hull formed by those of the master UAVs. Finally, some numerical simulations are provided to verify the effectiveness of the theoretical results.

Natural Interaction Techniques for an Unmanned Aerial Vehicle System

This article provides an overview of existing interaction techniques for controlling unmanned aerial vehicle (UAV) systems. This work focuses on user interfaces with nontraditional input modalities, such as gestures, speech, and gaze direction. Although the authors analyze interaction with UAV systems, most of the findings can be applied to human-robot interaction in general. The authors report on interaction techniques employed to control single as well as multiple UAV systems, define intuitiveness of input vocabularies in the considered context, and introduce a new classification scheme based on the mental models underlying the interaction vocabulary. This article is part of a special issue on drones.

Fault tolerant cooperative control for multiple unmanned aerial vehicle systems with plugging operations

A tracking problem for a group of multiple unmanned aerial vehicle (Multi-UAV) systems with agent faults is investigated. A neighbouring rule-based cooperative control algorithm is proposed such that the Multi-UAV systems can follow the common reference signals in a fault free situation. Once in the presence of faults that change the dynamics of the agents, a fault tolerant cooperative control strategy based on the plugging operations (with a minor adjustment of connection) is employed in order to make each agent continue to follow the reference signals without increasing the number of weak points. Moreover, the utilised plugging operations do not need to reconfigure any individual’s self control law or stop the faulty agents. Simulation results show the effectiveness of the proposed methods.

A self-organized search and attack algorithm for multiple unmanned aerial vehicles

This article presents a novel distributed algorithm for multiple unmanned aerial vehicles (UAVs) to solve the online search–attack mission self-organization problem under adversarial environment. The distributed search–attack mission self-organization algorithm (SAMSOA) divides the global optimization problem into some local optimization problems. Each UAV is considered as a subsystem and is assigned a separate processor to solve its local optimization problem. Meanwhile, the information exchange between UAVs can help each subsystem make the optimal decision for the multiple UAVs system. The SAMSOA algorithm consists of a normal flight mode and a threat avoidance mode. In the normal flight mode, the search–attack mission is modeled to maximize the surveillance coverage rate and minimize the targets' existence time. Then, the improved distributed ant colony optimization (ACO) algorithm is designed to generate path points. Finally, a Dubins curve is used to connect the path points smoothly. In the threat avoidance mode, the path of avoiding a threat is generated based on Dubins curve. A series of simulations are carried out to verify the online application of the proposed SAMSOA algorithm.

Modeling and optimization of multiple unmanned aerial vehicles system architecture alternatives.

Unmanned aerial vehicle (UAV) systems have already been used in civilian activities, although very limitedly. Confronted different types of tasks, multi UAVs usually need to be coordinated. This can be extracted as a multi UAVs system architecture problem. Based on the general system architecture problem, a specific description of the multi UAVs system architecture problem is presented. Then the corresponding optimization problem and an efficient genetic algorithm with a refined crossover operator (GA-RX) is proposed to accomplish the architecting process iteratively in the rest of this paper. The availability and effectiveness of overall method is validated using 2 simulations based on 2 different scenarios.

Experimental Evaluation of Unmanned Aerial Vehicle System Software Based on the TMO Model

Over the past few decades, a considerable number of studies have been conducted on the technologies to build an UAV (Unmanned Aerial Vehicle) control system. Today, focus in research has moved from a standalone control system towards a network-centric control system for multiple UAV systems. Enabling the design of such complex systems in easily understandable forms that are amenable to rigorous analysis is a highly desirable goal. In this paper, we discuss our experimental evaluation of the Time-triggered Message-triggered Object (TMO) structuring scheme in the design of the UAV control system. The TMO scheme enables high-level structuring together with design-time guaranteeing of accurate timings of various critical control actions with significantly smaller efforts than those required when using lowerlevel structuring schemes based on direct programming of threads, UDP invocations, etc. Our system was validated by use of environment simulator developed based on an open source flight simulator named FlightGear. The TMO-structured UAV control software running on a small computing platform was easily connected to a simulator of the surroundings of the control system, i.e., the rest of the UAV and the flight environment. Positive experiences in both the TMO-structured design and the validation are discussed along with potentials for future expansion in this paper.