UAV Systems and Swarm Robotics

The unstable nature of the dynamics of Unmanned Aerial Vehicles (UAVs) might significantly increase the complexity of their control strategies. In addition, some UAV systems require robust and fast stabilization to perform certain maneuvers. In particular, tail-sitter UAVs, which combine the advantages of fixed-wing aircraft and rotorcraft, require the development of novel control strategies. In [1], different nonlinear control solutions are explored for the problem of stabilizing a tail-sitter when hovering. Regarding the compared control strategies, the authors propose a novel control scheme based on Nonlinear Dynamic Inversion. The control strategies were implemented in a microcontroller and validated in a Hardware-in-the-Loop scenario. Then, they were used to stabilize the aircraft in experimental flight. In recent years, the application of vision-based control to UAVs has been shown to be an effective approach. Cameras are light, low-cost sensors that provide meaningful information for UAV control. In [2], the authors present a computer vision-based system for the landing and obstacle avoidance of a quadcopter. They propose a low-cost embedded system for quadcopter navigation to improve energy efficiency and maneuvering. The system relies on additional LIDAR sensors for measuring altitude and distance to objects. This paper was developed as part of research projects related to environmental monitoring, particularly for volcano surveillance applications.