相关论文: Multi-Agent Meta-Advisor for UAV Fleet Trajectory …

Persistent monitoring of dynamic targets is essential in real-world applications such as disaster response, environmental sensing, and wildlife conservation, where mobile agents must continuously gather information under uncertainty. We…

Prompt-based offline methods are commonly used to optimize large language model (LLM) responses, but evaluating these responses is computationally intensive and often fails to accommodate diverse response styles. This study introduces a…

Due to changes in model dynamics or unexpected disturbances, an autonomous robotic system may experience unforeseen challenges during real-world operations which may affect its safety and intended behavior: in particular actuator and system…

Propelled by multi-user MIMO (MU-MIMO) technology, unmanned aerial vehicles (UAVs) as mobile hotspots have recently emerged as an attractive wireless communication paradigm. Rate adaptation (RA) becomes indispensable to enhance UAV…

Unmanned aerial vehicle (UAV) base stations (BSs) are reliable and efficient alternative to full fill the coverage and capacity requirements when the backbone network fails to provide such requirements due to disasters. In this paper, we…

Multi-Agent Path Finding (MAPF) involves determining paths for multiple agents to travel simultaneously and collision-free through a shared area toward given goal locations. This problem is computationally complex, especially when dealing…

We present a resilient deep neural network (DNN) framework for decentralized transport and coverage using uncrewed aerial systems (UAS) operating in $\mathbb{R}^n$. The proposed DNN-based mass-transport architecture constructs a layered…

Multi-agent systems provide a powerful way to extend large language models (LLMs) by decomposing a complex task into specialized subtasks handled by different agents. However, their performance is often hindered by error propagation,…

Joint deployment of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has been shown to be an effective method to establish communications in areas affected by disasters. However, ensuring good Quality of Services (QoS)…

Since various types of unmanned aerial vehicles (UAVs) with different hardware capabilities are introduced, we establish a foundation for the multi-layer aerial network (MAN). First, the MAN is modeled as K layer ANs, and each layer has…

This paper proposes a hierarchical trajectory planning framework for UAVs operating under adversarial jamming conditions. Leveraging Bayesian Active Inference, the approach combines expert-generated demonstrations with probabilistic…

The challenge of efficient target searching in vast natural environments has driven the need for advanced multi-UAV active search strategies. This paper introduces a novel method in which global and local information is adeptly merged to…

In this article, we report on the efficiency and effectiveness of multiagent reinforcement learning methods (MARL) for the computation of flight delays to resolve congestion problems in the Air Traffic Management (ATM) domain. Specifically,…

We investigate the performance of unmanned aerial vehicle (UAV)-based networks in urban environments characterized by blockages, focusing on their capability to support the service demands of mobile users. The UAV-base stations (UAV-BSs)…

In recent years, unmanned aerial vehicles (UAVs) assisted mobile edge computing systems have been exploited by researchers as a promising solution for providing computation services to mobile users outside of terrestrial infrastructure…

In this paper, a novel machine learning (ML) framework is proposed for enabling a predictive, efficient deployment of unmanned aerial vehicles (UAVs), acting as aerial base stations (BSs), to provide on-demand wireless service to cellular…

Robust beamforming design under imperfect channel state information (CSI) is a fundamental challenge in multiuser multiple-input multiple-output (MU-MIMO) systems, particularly when the channel estimation error statistics are unknown.…

The multi-robot adaptive sampling problem aims at finding trajectories for a team of robots to efficiently sample the phenomenon of interest within a given endurance budget of the robots. In this paper, we propose a robust and scalable…

Recently, the unmanned aerial vehicles (UAVs) have been widely used in real-time sensing applications over cellular networks, which sense the conditions of the tasks and transmit the real-time sensory data to the base station (BS). The…

Medical diagnosis using Large Multimodal Models (LMMs) has gained increasing attention due to capability of these models in providing precise diagnoses. These models generally combine medical questions with visual inputs to generate…