Autonomous Micro Aerial Vehicles: Methods and Applications Ⅱ
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".
Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 318
Special Issue Editor
Interests: robotics and AI; control applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Micro aerial vehicles (MAVs) are dominating the current focus of resaerch in robotics. Their simplicity in the mechanical structure and the ability to provide a fast deployment and translation in a 3D space, create a novel set of potential radical applications that have never appeared before. Moreover, endowing MAVs with proper sensor suites establishes them as a powerful aerial tool for a wide span of applications in infrastructure inspection, public safety surveillance, search and rescue missions, and in the mining and similar industries. MAVs have the profound potential to decrease risks to human life and execution time, and increase the efficiency of the overall process, especially when compared to conventional robotic technologies.
In all the previous cases, autonomy is the enabling factor for these envisioned MAV capabilities. An autonomy that comes in the form of robust perception of the environment, multi-sensorial localization, global and local planning of a mission, as well as autonomy in the coordination and cooperation among multiple aerial vehicles. These aspects of advanced and robust autonomy are trending in the research community and are still open research directions. Thus, the second volume of the Special Issue "Autonomous Micro Aerial Vehicles: Methods and Applications" will focus at the autonomy directions of MAVs for pushing further the bounds of this technology, while enabling a rapid adoptions from the corresponding industries. As such, the topics of interest of this issue include (but are not limited to):
- Autonomous aerial robot applications for key enabling technologies;
- Autonomy Collaborative robots for performing complex tasks;
- Sensor fusion for robust localization;
- Autonomous navigation, mapping, and SLAM;
- Novel autonomous planning and coverage methods;
- Obstacle perception and reactive navigation;
- Multi-agent planning, mapping and localization methods;
- Vision-based control and visual tracking;
- Reinforcement learning autonomous task execution;
- ML approaches in autonomy for MAVs.
Prof. Dr. George Nikolakopoulos
Guest Editor
Manuscript Submission Information
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Keywords
- Autonomous MAVs
- Control
- Perception
- Navigation
- Planning
- Aerial Manipulation
- Multi Aerial Agents
- Reinforcement learning
- Sensors
- Object detection and tracking.
