Drone Mission Planning

We are pleased to invite you to submit your papers to this Drones Special Issue on Drones Mission Planning.

Drones, also called unmanned aerial vehicles (UAV), are extremely popular and useful for many tasks. In the last decade, the use of UAVs has become very popular, and it is expected to grow even more over the coming years. This growth is due to interest from both the industrial and research communities. Industries, such as agriculture or forestry, are attracted by the different potential applications, which include surveillance, disaster, and crisis management; while the research community is also interested in UAV due to the challenging problems that must be faced by different fields such as human–machine interfaces, augmented reality, and mission planning.

The field of mission planning has expanded substantially in recent years, due to the boom of artificial intelligence methods and their applications to different real-life problems, including mission planning for UAVs. In this context, different methods including black-box optimization techniques (including metaheuristics) and decision-making methods have been widely used to tackle the complexity of the mission planning problem, where one or several UAVs must perform different tasks in some geographic area within a specific time interval.

One of the most challenging problems to face in this topic is the effort required for replanning a mission in real-time. Very few works have been published in this area, due to the difficulty of the problem and the limitations in the computational power of current UAV systems. Nevertheless, advancement in this area is a key point to reduce the workload of UAV operators.

Within this context, we invite papers focusing on current advances in the area of mission planning and replanning for UAVs.

Related References:

Karaman, S. and Frazzoli, E. “Linear temporal logic vehicle routing with applications to multi‐UAV mission planning.” Int. J. Robust Nonlinear Control (2011) 21: 1372. https://doi.org/10.1002/rnc.1715

Evers, L., Dollevoet, T., Barros, A.I., et al. “Robust UAV mission planning.” In: Annals of Operations Research (2014) 222: 293. https://doi.org/10.1007/s10479-012-1261-8

Ramirez-Atencia, C., Bello-Orgaz, G., R-Moreno, M.D. et al. “Solving complex multi-UAV mission planning problems using multi-objective genetic algorithms.” In: Soft Computing (2017) 21: 4883. https://doi.org/10.1007/s00500-016-2376-7

Qiao, Y., Yang, J., Zhang, Q. et al. "Multi-UAV Cooperative Patrol Task Planning Novel Method Based on Improved PFIH Algorithm." In: IEEE Access (2019) 7: 167621. https://doi.org/10.1109/ACCESS.2019.2952877

Dr. Cristian Ramírez Atencia
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. 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.

• Application of artificial intelligence methods for the resolution of the UAV mission planning problem
• Techniques for the minimization of path planning in surveillance and target detection missions
• Black-box optimization methods and metaheuristics applied to the resolution of mission planning problems
• Multi-agent and swarm systems for the coordination and planning of missions
• Large-scale aerial datasets and standardized benchmarks of missions for the application of planning algorithms
• Mission planning in uncertain and dynamic environments
• Robust mission planning and mission replanning for UAVs
• Decision-making techniques for the selection of mission plans