Recent Advancements in Unmanned Aerial Vehicles
A project collection of Applied Sciences (ISSN 2076-3417). This project collection belongs to the section "Aerospace Science and Engineering".
Papers displayed on this page all arise from the same project. Editorial decisions were made independently of project staff and handled by the Editor-in-Chief or qualified Editorial Board members.
Viewed by 2228Editors
Interests: unmanned aerial vehicles; autonomous and multi-agent systems; control systems; probabilistic risk assessment; applications to robotic and aerospace systems
Special Issues, Collections and Topics in MDPI journals
Interests: unmanned aerial vehicles; decision making on multi-agent systems; distributed sensing and estimation; data-centric guidance and control
Special Issues, Collections and Topics in MDPI journals
Project Overview
Dear Colleagues,
Unmanned aerial vehicles (UAVs) are now recognized as very useful tools to replace, help or assist humans in tasks such as inspection and monitoring, surveillance, search and rescue, exploration, logistics and transportation, etc. Practical uses for such missions in both civilian and defense contexts have experienced significant growth thanks to recent technological progresses. Nevertheless, some challenges and open issues remain to ensure full operational uses of UAVs.
This Special Issue aims to present recent advances in technologies and algorithms to improve the autonomy, reliability and safety of UAVs. Topics of interest include but are not limited to: advanced guidance, navigation and control algorithms; autonomy and decision making; perception and multi-sensor fusion for robust navigation; networked swarms; unmanned aerial system traffic management (UTM); new concepts and designs of vehicles; smart sensors for UAVs; new applications and field experiments; reliability, safety and risk assessment.
Dr. Sylvain Bertrand
Prof. Dr. Hyo-sang Shin
Guest Editors
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Keywords
- unmanned aerial vehicles
- unmanned aerial system traffic management
- guidance, navigation and control
- autonomy, perception, decision making
- multiple agent systems
- networked swarms
- reliability, safety, risk assessment