Air Traffic Management for Collaborative Routing of Unmanned Aerial Vehicles via Potential Fields

2024-03-17 · Josue N. Rivera, Dengfeng Sun

Aerial cargo transport is anticipated to play a pivotal role in the distribution of goods within urban environments. The shift is propelled by the surge in e-commerce, the imperative to deliver essential supplies to isolated areas, and the growing demand for expedited and more accessible deliveries. Our research introduces a quantifiable standard for defining routing restrictions for Unmanned Aircraft System Traffic Management (UTM) using the concept of repulsive potential fields. Furthermore, we propose a scalable infrastructure that facilitates collaborative routing of cargo Unmanned Aerial Vehicles (UAVs) by independent shareholders. The practicality of the infrastructure is validated through a functional prototype implemented at a national scale.

📄 PDF Abstract BibTeX arXiv:2403.11086

Code (1)

wzjoriv/lar-backend

Tasks

Management

Collaborative Wideband Spectrum Sensing and Scheduling for Networked UAVs in UTM Systems

2023-08-09 · Sravan Reddy Chintareddy, Keenan Roach, Kenny Cheung, Morteza Hashemi

In this paper, we propose a data-driven framework for collaborative wideband spectrum sensing and scheduling for networked unmanned aerial vehicles (UAVs), which act as the secondary users to opportunistically utilize de…

Management Multi-class Classification Reinforcement Learning (RL)Scheduling

Federated Learning-based Collaborative Wideband Spectrum Sensing and Scheduling for UAVs in UTM Systems

2024-06-03 · Sravan Reddy Chintareddy, Keenan Roach, Kenny Cheung, Morteza Hashemi

Dataset Generation Federated Learning Management Reinforcement Learning (RL)+1

Solving routing problems for multiple cooperative Unmanned Aerial Vehicles using Transformer networks, vol. 122, pp. 106085, 2023

2023-03-09 · Engenieering of Artificial Intelligence Applications 2023 3 · Daniel Fuertes, Carlos R. del Blanco, Fernando Jaureguizar, Juan José Navarro 외

Missions involving Unmanned Aerial Vehicle usually consist of reaching a set of regions, performing some actions in each region, and returning to a determined depot after all the regions have been successfully visited or…

Combinatorial Optimization Deep Reinforcement Learning Multi-agent Reinforcement Learning

Decentralized traffic management of autonomous drones

2023-12-18 · Boldizsár Balázs, Tamás Vicsek, Gergő Somorjai, Tamás Nepusz 외

Coordination of local and global aerial traffic has become a legal and technological bottleneck as the number of unmanned vehicles in the common airspace continues to grow. To meet this challenge, automation and decentra…

Management

Traffic Simulation in Ad Hoc Network of Flying UAVs with Generative AI Adaptation

2026-01-01 · Andrii Grekhov, Volodymyr Kharchenko, Vasyl Kondratiuk arxiv

The purpose of this paper is to model traffic in Ad Hoc network of Unmanned Aerial Vehicles and demonstrate a way for adapting communication channel using Artificial Intelligence. The modeling was based on the original m…