Large multi-UAV mission systems operate over time-varying communication graphs with heterogeneous platforms, where classical distributed task assignment may incur excessive message passing and suboptimal task–resource matching. To address these...
In UAV swarm adversarial applications, multi-agent task allocation requires high-level reasoning and accurate decision-making in dynamic environments. Although large language models (LLMs) have shown strong performance in zero-shot reasoning, they ca...
The growing affordability, autonomy, and swarming of small unmanned aerial vehicles (UAVs) turn low-altitude defense from single-shot interception into a multi-node cooperative decision problem, in which the loss of sensing, coordination, or engageme...
Decentralized task allocation among multiple Unmanned Aerial Vehicles (UAVs) is a critical NP-hard combinatorial optimization problem for enabling autonomous swarms to operate without central supervision. Multi-UAV research has advanced distributed a...
Unmanned aerial vehicles (UAVs) play a crucial role in enhancing search and rescue (SAR) operations by accessing inaccessible areas, accomplishing challenging tasks, and providing real-time monitoring and modeling in situations where human presence i...
Mission planning is the guidance for a UAV team to perform missions, which plays the most critical role in military and civil applications. For complex tasks, it requires heterogeneous cooperative multi-UAVs to satisfy several mission requirements. M...
Unmanned aerial vehicles (UAVs), commonly known as drones, offer unprecedented flexibility for complex missions such as area surveillance, search and rescue, and cooperative inspection. This paper presents a unified evaluation framework for the compa...
In the rapidly evolving field of aerial robotics, the coordinated management of multiple unmanned aerial vehicle (multi-UAV) systems to address complex and dynamic environments is increasingly critical. Multi-UAV systems promise enhanced efficiency a...
Unmanned aerial vehicles (UAVs) play an increasingly vital role in maritime search and rescue (SAR) because they can be deployed quickly, cover large ocean areas, and operate without exposing human crews to risk. Compared with single platforms, multi...
Efficient UAV path-planning algorithms significantly improve inspection efficiency and reduce costs. However, due to the limitation of battery capacity, the endurance of existing UAVs is limited, making it difficult for them to directly undertake inf...
With the rapid development of edge-intelligence systems, multi-UAV platforms have become vital for large-scale 3D reconstruction. However, efficient task scheduling remains a critical challenge due to constraints on UAV energy, communication range, a...
In multi-UAV cooperative tasks, dynamic communication topologies and resource heterogeneity present significant challenges for distributed task allocation, leading to high communication overhead and poor task-resource matching, which in turn increase...
The rapid advancement of unmanned aerial vehicle (UAV) technology has led to its widespread adoption in military reconnaissance, disaster monitoring, environmental inspection, and related fields. However, a single UAV often faces limitations when exe...
With multi-sensors embedded, flexible unmanned aerial vehicles (UAVs) can collect sensory data and provide various services for all walks of life. However, limited computing capability and battery energy put a great burden on UAVs to handle emerging...
Multi-UAV multi-sensor cooperative detection is critical for situational awareness in complex environments with stationary known targets. To overcome the shortcomings of existing task allocation models in fine-grained cooperation, stealth constraints...
Large-scale multi-UAV reconnaissance task allocation requires efficient optimization of coupled vehicle assignments and target visit orders. This study presents HI-ALWPA, a cooperative island-parallel extension of the Adaptive Lévy Wolf Pack A...
Unmanned aerial vehicles (UAVs) are extensively employed for urban image captures and the reconstruction of large-scale 3D models due to their affordability and versatility. However, most commercial flight software lack support for the adaptive captu...
As UAV popularity soars, so does the mission planning associated with it. Classical planning approaches suffer from the triple problems of decoupling of task assignment and path planning, poor real-time and scalability, and limited adaptability. Aimi...
To address the challenges of unbalanced task allocation, high inter-UAV collision risks, and lagging interception guidance in multi-UAV cooperative missions within complex urban low-altitude environments, a cooperative interception strategy integrati...
Mountain search-and-rescue missions require multiple unmanned aerial vehicles (UAVs) to cooperate efficiently under limited communication and constrained operational resources. Existing multi-UAV search methods often rely on centralized task allocati...
To address the uneven distribution of the Pareto front and insufficient convergence in multi-UAV task allocation, this paper proposes GrEAPSO, an improved algorithm that hybridizes Particle Swarm Optimization (PSO) with Genetic Algorithm (GA). GrEAPS...
Cooperative multi-UAV clusters have been widely applied in complex mission scenarios due to their flexible task allocation and efficient real-time coordination capabilities. The Air Command Aircraft (ACA), as the core node within the UAV cluster, is...
Multi-UAV cooperative delivery is a key technology for intelligent low-altitude logistics, with applications in mountainous-area transport, urban last-mile delivery, and emergency resupply. In complex three-dimensional (3D) low-altitude environments,...
Dynamic events, such as new task arrivals, UAV failures, and changes in task time windows, require timely updates to task allocation plans in multi-UAV systems. Global replanning provides broad flexibility for feasibility recovery, but it may also mo...
With the development of the Internet of Things (IoT), IoT devices are increasingly being deployed in scenarios with large footprints, remote locations, and complex geographic environments. In these scenarios, base stations are usually not easily depl...
The rapid advancement of intelligent unmanned systems has brought new opportunities to mobile crowd sensing (MCS). Compared with traditional homogeneous frameworks, heterogeneous air-ground collaborative multi-agent frameworks consisting of unmanned...
In large-scale Unmanned Aerial Vehicle (UAV) and task environments—particularly those involving obstacles—dimensional explosion remains a significant challenge in Multi-Robot Task Allocation (MRTA). To this end, a novel heuristic MRTA fra...
This paper primarily studies the path planning problem for UAV formations guided by semantic map information. Our aim is to integrate prior information from semantic maps to provide initial information on task points for UAV formations, thereby plann...
Unmanned aerial vehicles (UAVs) have increasingly become integral to multi-access edge computing (MEC) due to their flexibility and cost-effectiveness, especially in the B5G and 6G eras. This paper aims to enhance the quality of experience (QoE) in l...
As a flight tool integrating carrier and reconnaissance, unmanned aerial vehicles (UAVs) are applied in various fields. In recent years, mission planning and path optimization have become the most important research focuses in the field of UAVs. With...
Traditional multi-access edge computing (MEC) often has difficulty processing large amounts of data in the face of high computationally intensive tasks, so it needs to offload policies to offload computation tasks to adjacent edge servers. The comput...
With the increasing deployment of unmanned systems in maritime patrol, coastal monitoring, and environmental mapping, achieving effective UAV-USV collaboration in dynamic environments remains challenging. This paper proposes an edge-intelligence-driv...
To address the dynamic target allocation and resource scheduling problems of multiple High-Energy Laser Systems (HELSs) in defending critical infrastructure against large-scale heterogeneous UAV swarm penetration, this paper proposes a soft–har...
Safe-separation-and-collision-avoidance unmanned aerial vehicle (UAV) swarms are increasingly used for inspection, emergency response, environmental monitoring, and search-and-rescue support in cluttered airspace where communication links may be dela...
With the rapid growth of demands in marine resource exploitation, environmental monitoring, and maritime safety, cooperative operations based on Unmanned Surface Vehicles (USVs) and Unmanned Aerial Vehicles (UAVs) have emerged as a promising paradigm...
Maritime dynamic observation missions, such as environmental monitoring, marine ranching inspection, and emergency response, typically require large-scale and high-efficiency operations in complex and variable maritime environments. Unmanned Surface...
As UAVs are increasingly deployed in complex scenarios such as disaster monitoring, emergency rescue, and power-line inspection, traditional command and control systems face severe challenges in intelligent decision-making, resource allocation, and e...
Cooperative task planning for amphibious firefighting UAVs deployed across multiple bases is challenging because of complex resource coupling, evolving fire conditions, and real-time decision requirements. This study proposes an H-MAPPO-LSTM method w...
Heterogeneous unmanned aerial vehicle (UAV) swarms are becoming critical components of next-generation non-terrestrial networks, enabling tasks such as communication relay, spectrum monitoring, cooperative sensing, and navigation. Yet, their heteroge...
Multi-agent systems (MASs), with unmanned aerial vehicles (UAVs) as a representative embodiment, have become increasingly vital in time-sensitive disaster response scenarios, where multiple agents must collaborate to execute “observe-and-interv...
Task planning involving multiple unmanned aerial vehicles (UAVs) is one of the main research topics in the field of cooperative unmanned aerial vehicle control systems. This is a complex optimization problem where task allocation and path planning ar...
To address the limitations of the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm in autonomous control tasks including low convergence efficiency, poor training stability, inadequate adaptability of confrontation strategies, and ch...
To address load–energy dynamic coupling in heterogeneous unmanned aerial vehicle (UAV) emergency rescue, this paper proposes an energy-coupled heterogeneous UAV task allocation (EC-HUTA) model that explicitly characterizes nonlinear interdepend...
The cooperative airdrop of UAV swarms by multiple transport aircraft creates a large-scale multi-agent planning problem. The mission involves heterogeneous aircraft, multi-visit airdrop areas, strict time windows, and threat-aware flight paths. To ad...
Large-scale maritime activity, persistent shipping incidents, and complex marine environments continue to place substantial demands on maritime search and rescue (MSAR). Current MSAR systems do not fully capitalize on the complementary strengths of u...
With the growing applications of maritime unmanned systems in environmental monitoring, ocean patrol, and emergency response, achieving efficient multi-platform cooperation in complex and dynamic marine environments remains a critical challenge. Unma...
To address the task-grouping problem for air–ground integrated Unmanned Aerial Vehicle (UAV) swarm missions in three-dimensional (3D) environments, this study proposes a data-preprocessing and hybrid initialization clustering method based on 3D...
The Internet of Things (IoT) has promoted emerging applications that require massive device collaboration, heavy computation, and stringent latency. Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) systems can provide flexible servi...
This work formulates and solves the actual problem of studying the logistics of unmanned aerial vehicle (UAV) operations in facility security planning. The study is related to security tasks, including perimeter control, infrastructure condition moni...
Rapid preliminary reconnaissance of Critical Transportation Hubs (CTHs) by UAV swarms is vital during post-disaster rescue operations. However, limited camera fields of view, large heading variances, and GNSS multipath errors near massive steel-concr...
of 2