Special Issue "Navigation, Control and Mission Planning Advances for Safe, Efficient and Autonomous Drones"
A special issue of Drones (ISSN 2504-446X).
Deadline for manuscript submissions: 30 November 2023 | Viewed by 8702
Interests: fault tolerance; control; motion estimation; system identification; aircraft; spacecraft
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; IoT; fault tolerance; fault diagnosis; optimisation; autonomous maintenance; drones
Interests: attitude determination and control, UAV, control, satellite technology, spacecraft propulsion, autonomy
Special Issues, Collections and Topics in MDPI journals
We are pleased to invite you to submit manuscripts to the MDPI Drones Special Issue entitled “Navigation, Control and Mission Planning Advances for Safe, Efficient and Autonomous Drones”
Drones have considerably evolved in the last two decades, with an increased emphasis on safety, autonomy and performance to perform a wide range of missions. Air, ground, marine and even space vehicles are currently used for applications from land surveys to precision agriculture, disaster monitoring, forestry and other applications in society and in several industries.
Advances in navigation, control, as well as other enabling technologies from data handling to communication systems are necessary to safely meet the increased demand for autonomy. In a single drone, these challenges include the ability to maintain admissible or optimal flight performance using limited computational and power resources with the ability to handle faults, anomalies, as well as vehicle and mission constraints such as drone endurance and operational envelopes.
In UAV swarms and formations, the challenges extend to the need for mission-level architectures to coordinate the path planning and path following using centralised or decentralised navigation, control and communication systems, including ground station–vehicle communications.
The state-of-the-art methods used to address challenges in single and distributed drone systems are often based on advances in the navigation and control theory, increasingly based on machine learning, or a combination of those two approaches, such as artificial intelligence (AI)-enhanced navigation and control. Advances in new technologies such as the Internet of things and Detect and Avoid are also increasingly exploited to enhance navigation and control safety and performance.
This Special Issue will therefore bring together papers which describe recent research in the navigation, control and mission planning of drones, including ground, air, marine or space vehicles. Papers with theoretical, simulation and practical experimental results in this field are all encouraged. This includes review papers, tutorials, as well as original research papers.
Possible topics include, but are not limited to:
- Advances in path planning and path following methods for drones;
- Machine learning-based navigation and control or mission planning in drones;
- Unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs), and spacecraft navigation and control;
- Adaptive, optimal or robust control of drones;
- Control under vehicle, operational and collision avoidance constraints;
- Sensor fusion for drone navigation;
- Hybrid and multimode navigation and control systems;
- Linear and nonlinear motion estimation using filtering, observer-based and recursive methods;
- Fault detection, isolation and recovery in drones;
- Multi-vehicle networks and communication systems for coordinated drone navigation and control;
- Coordinated navigation and control of formations and swarms of aerial, ground or space vehicles;
- Distributed systems with different types of vehicles (eg. ground and air vehicles, air and space vehicles);
- Advances in computer and data handling systems for increased navigation and control autonomy;
- Dynamical modeling and/or control for emerging drone designs (hybrid UAV designs, eVToL);
- Internet of thing applications in drone navigation and control;
- System identification for drones.
Dr. Nadjim Horri
Dr. Samir Khan
Prof. Dr. Vaios Lappas
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- path following
- machine learning