Multi Rotor
Multi-rotor aerial vehicles (MRAVs), encompassing drones and other similar platforms, are the focus of intense research aimed at improving their control, autonomy, and application in diverse fields. Current research emphasizes enhancing control algorithms, such as model predictive control (MPC) and feedback linearization, often incorporating machine learning for disturbance estimation and improved trajectory planning, particularly in complex or dynamic environments. These advancements are driving progress in applications ranging from infrastructure inspection and search and rescue to cooperative communication and human-swarm interaction, significantly impacting robotics, communication systems, and various industrial sectors.
Papers
Autonomous Aerial Filming With Distributed Lighting by a Team of Unmanned Aerial Vehicles
Vít Krátký, Alfonso Alcántara, Jesús Capitán, Petr Štěpán, Martin Saska, Aníbal Ollero
Autonomous Reflectance Transformation Imaging by a Team of Unmanned Aerial Vehicles
Vít Krátký, Pavel Petráček, Vojtěch Spurný, Martin Saska
Optimum Trajectory Planning for Multi-Rotor UAV Relays with Tilt and Antenna Orientation Variations
Daniel Bonilla Licea, Giuseppe Silano, Mounir Ghogho, Martin Saska
A Perception-Aware NMPC for Vision-Based Target Tracking and Collision Avoidance with a Multi-Rotor UAV
Andriy Dmytruk, Giuseppe Silano, Davide Bicego, Daniel Bonilla Licea, Martin Saska