Unmanned Aerial Systems

1. UAS System Design<br>2. UAS Control systems<br>3. Hybrid control of UAS<br>4. Obstacle and collision avoidance of UAS<br>5. UAV onboard data storage, transmission and retrieval<br>6. Kalman and Particle filtering and other advanced techniques for motion sensor data fusion<br>7. Simultaneous Localization and Mapping (SLAM)<br>8. Single/multiple IMU–Vision-based navigation and orientation<br>9. Autopilots and navigation: standard and advanced solutions for navigation integrity<br>10. Integration of UAS into the Internet<br>11. IoT applications using UAS<br>12. Safety issues of UAS<br>13. Ultra-Wide Band (UWB) localization<br>14. Security threats of UAS<br>15. UAS public deployment challenges<br>16. UAS for cloud robotics<br>17. Deep neural networks (DNN) for field aerial robot perception (e.g., object detection, or semantic classification for navigation)<br>18. Recurrent networks for state estimation and dynamic identification of aerial vehicles<br>19. Deep-reinforcement learning for aerial robots (discrete-, or continuous-control) in dynamic environments<br>20. Learning-based aerial manipulation in cluttered environments<br>21. Decision making or task planning using machine learning for field aerial robots<br>22. Long-term ecological monitoring based on UAVs<br>23. Ecological Integrity parameters mapping<br>24. Rapid risk and disturbance assessment using drones<br>25. Ecosystem structure and processes assessment by using UAVs