Unmanned Aircraft System Detection and Deconfliction

Dear Colleagues,

The emergence of Uncrewed Aircraft Systems (UAS) in aerospace highlights the need for a number of enabling automated technologies that can support safe and reliable operations within the airspace. Airspace integration requires reliable and robust navigation and deconfliction methods. Traffic management, including collision avoidance and deconfliction capabilities at the pre-flight and on-flight stages will address the problem of separation from other aircraft and obstacles during a mission.

Although there is a considerable body of literature on the topic of collision avoidance in the robotics community, the complexity of the aerospace operating environment and requirements, in general, pose significant challenges for robust object detection and deconfliction. Many technical issues concerning sensing and perception, navigation and path planning, guidance and control, and collision avoidance need to be addressed for safe operation by automatic or autonomous uncrewed vehicles in the airspace, shared by multiple other actors.  

The airspace regulators in many jurisdictions have recently launched initiatives related to UAS traffic management, or UTM. Surveillance and deconfliction are cornerstones of these initiatives. Traditional and modern approaches from various disciplines of engineering and computer science and artificial intelligence have considered these problems, but they are still intriguing to the research and practitioner communities.

To advance the field of autonomous UAS and aerial robotics, this Special Issue is dedicated to the research theme of object detection and deconfliction. We are inviting theoretical and experimental contributions related to this theme, including but not limited to:

• Perception and multi-sensor fusion;
• Machine learning for object detection and classification;
• Integration of autonomous aerial vehicles in airspace;
• UAS traffic management (UTM);
• Detect and avoid methods and systems;
• UAS deconfliction in airspace.

Dr. Iraj Mantegh
Guest Editor

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. Aerospace 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 2400 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.

• uncrewed aircraft systems (UAS)
• drone
• path planning
• object detection
• deconfliction
• navigation
• collision avoidance
• obstacle avoidance
• UAS traffic management (UTM)
• AI machine learning