Heterogeneous UAV Based on Machine Learning
Special Issue Information
Dear Colleagues,
The term "heterogeneous UAVs" involves various components of UAV communication, networking, formation, and path planning. The advanced control strategies, such as the ACO algorithm, fuzzy control, and Bayesian network, have now been implemented on the quad-rotor UAV's dynamic programming system in recent years, with good results. This has led a growing number of researchers to consider combining advanced control strategies with traditional controls, simplifying the complex control systems and implementing it on small control systems can significantly enhance the stability of control. This technique may be used to dynamically adjust the controller parameters based on the output.
Despite this, UAV networks differ from terrestrial wireless networks in several respects, including highly dynamic network topologies, orbit or flight patterns, and weakly coupled nodes. Communication nodes because the power supply is limited, the airborne system must be energy-efficiently built. Overall, it is plausible to assert that when large amounts of data from various sources are integrated, machine learning-based algorithms may successfully identify useful links toward optimizing UAV.
This Special Issue, entitled "Heterogeneous UAV Based on Machine Learning" will present the latest trends in Heterogeneous UAVs with the aim of integrating and identifying machine learning based optimized algorithms to address it.
Review articles and original research articles are welcome. Topics of interests include, but are not limited to, the following:
Machine Learning-Based Model Predictive Control
Distributed Optimization of Heterogeneous UAV
Computational complexity method for tracking drone
Multi-UAV platform technology
Real-time monitoring technology for UAV
Design of remote sensing by unmanned systems
UAV-assisted 6G communications
Integrated sensing and communications
Real-time multi-agent systems
Learning and adaptation in Heterogeneous UAV
Dr. Mohammad Shabaz
Dr. Azeem Irshad
Dr. Abolfazl Mehbodniya
Guest Editors