A fully actuated quadrotor UAV with a propeller tilting mechanism: Modeling and control

Equipped with four actuators, quadrotor Unmanned Aerial Vehicles belong to the family of underactuated systems. The lateral motion of such platforms is strongly coupled with their orientation and consequently it is not possible to track an arbitrary 6D trajectory in space. In this paper, we propose a novel quadrotor design in which the tilt angles of the propellers with respect to the quadrotor body are being simultaneously controlled with two additional actuators by employing the parallelogram principle. Since the velocity of the controlled tilt angles of the propellers does not appear directly in the derived dynamic model, the system cannot be static feedback linearized. Nevertheless, the system is linearizable at a higher differential order, leading to a dynamic feedback linearization controller. Simulations confirm the theoretical findings, highlighting the improved motion capabilities with respect to standard quadrotors

Obstacle Detection, Tracking and Avoidance for a Teleoperated UAV

In this paper, we present a collision-free indoor navigation algorithm for teleoperated multirotor Unmanned Aerial Vehicles (UAVs). Assuming an obstacle rich environment, the algorithm keeps track of detected obstacles in the local surroundings of the robot. The detection part of the algorithm is based on measurements from an RGB-D camera and a Bin-Occupancy filter capable of tracking an unspecified number of targets. We use the estimate of the robot’s velocity to update the obstacles state when they leave the direct field of view of the sensor. The avoidance part of the algorithm is based on the Model Predictive Control approach. By predicting the possible future obstacles states, it filters the operator commands to prevent collisions. The method is validated on a platform equipped with its own computational unit, which makes it selfsufficient in terms of external CPUs