Path Planning for Drone Operations under Varying Environments and Platforms

Dear Colleagues, 

Drones have been actively considered in a wide spectrum of applications and case studies. Although their underlying potential is clear, they are often used as simple camera and sensor carriers or data collectors. On the other hand, more sophisticated drone applications have been demonstrated in simulation environments, though their implementation has led to insurmountable challenges that are not addressed or even identified in virtual schemes. Therefore, there is a clear necessity to focus on realistic objectives and paradigms to guide drone use towards safer, more robust and realistic conditions and to determine the plausibility of drone involvement in real-life applications. Addressing this gap may prove quite beneficial in increasing the acceptance and incorporation of drones in many other research areas and societal challenges and changing the mindset of researchers and academics.

This Special Issue aims to attract original studies concerning implementations, theoretical approaches, algorithms, applications and case studies on the following themes:

• Autonomous navigation, multimodal systems, indoor mapping and SLAM;
• Real-time, on-board processing for autonomous systems;
• Collaborative aerial, terrestrial and underwater systems and satellite platforms and mixed implementations;
• Machine learning and reinforcement learning for image and data processing;
• Planetary exploration and path planning;
• BIM and infrastructure inspection;
• Disaster area mapping and dynamic environments;
• Challenging agricultural, biodiverse and forest environments;
• Point cloud processing and lidar/photogrammetric integration;
• GNSS-denied and mixed environments and seamless positioning;
• Sensor integration and data collection.

Through this Special Issue, we would like to demonstrate novel perspectives and challenges in varying environments, platforms and requirements under which drones may operate. Seamless navigation in GNSS-denied and -enabled areas, the collaboration and sharing of information between different autonomous platforms and the ability of the drones to decide and define their course based on collected data and mission objectives are of particular interest. Novel implementations and theoretical approaches are encouraged as well as applications and case studies in various areas, including planetary exploration, infrastructure inspection, environmental data collection, and agrifood applications.

Dr. Panagiotis Partsinevelos
Guest Editor

Manuscript Submission Information

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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 planning
• autonomous systems
• GNNS-denied environments
• collaborative systems
• embedded systems
• point clouds
• machine learning
• reinforcement learning
• BIM
• navigation