Compared to other vertical take-off and landing (VTOL) systems, a tailsitter minimizes the number of actuators and moving parts necessary. The downside of having a minimalistic actuation is its inherent low fault-tolerance. The failure of an actuator usually results in a loss of controllability, resulting in a crash. In this paper we analyze possible actuator failures and the constraints they pose on the capabilities of the system. We further present light-weight adaptations to the nominal flight controller to make it fault-tolerant. The fault-tolerant controller is implemented on a small tailsitter VTOL aircraft and adjusted to the system by means of extensive experimental studies. Finally, the capabilities and performance under failures are demonstrated and analyzed.

To many unmanned aerial vehicle (UAV) designs, the lack of information about the wind speed and direction is a limiting factor in achieving robust outdoor flight. This paper addresses the problem of wind estimation onboard a hovering vertical take-off and landing (VTOL) tailsitter UAV. The proposed estimation framework makes use of the standard onboard sensor suite: inertial measurement unit (IMU), global positioning system (GPS) and a magnetometer. No additional airspeed sensor is needed. As a result, the autopilot is provided with an estimate of the wind velocity vector in the horizontal (north-east) plane. An aerodynamic model of the vehicle has been derived and used in a Kalman filter framework to estimate the horizontal wind velocity vector in real-time. The wind estimator has been implemented onboard the UAVs autopilot and validated in real flight. As a result, we successfully obtain the direction and speed of the wind with an estimation accuracy close to the accuracy range of the ground truth measurement. Furthermore, the derived grey-box model allows to generalise the framework to different airframes.

This paper shows a strategy based on passive force control for collaborative object transportation using Micro Aerial Vehicles (MAVs), focusing on the transportation of a bulky object by two hexacopters. The goal is to develop a robust approach which does not rely on: (a) communication links between the MAVs, (b) the knowledge of the payload shape and (c) the position of grasping point. The proposed approach is based on the master-slave paradigm, in which the slave agent guarantees compliance to the external force applied by the master to the payload via an admittance controller. The external force acting on the slave is estimated using a non-linear estimator based on the Unscented Kalman Filter (UKF) from the information provided by a Visual-Inertial (VI) navigation system. Experimental results (online video [1]) demonstrate the performance of the force estimator and show the collaborative transportation of a 1.2 m long object.

This paper addresses the problem of trajectory optimization for the transition of a Vertical Take-off and Landing (VTOL) tailsitter Unmanned Aerial Vehicle (UAV). The proposed strategy performs a model based optimization, where the model represents the closed-loop dynamics of the UAV with low-level control, ensuring attitude stabilization over the whole trajectory. We discuss the design of an optimization framework, vehicle modeling, and elaborate on the cost function construction. An additional feedback gain is implemented on the throttle channel with altitude discrepancies as its input to provide some level of robustness to wind disturbances. The overall approach is verified in simulation and experimental results with a focus on optimization of the back-transition (cruise-to-hover) of the Wingtra S100 VTOL tailsitter.

This paper addresses the challenges of the design, development and control of a new convertible VTOL tailsitter unmanned aerial vehicle that combines the advantages of both fixed wing and rotary wing systems. Wind tunnel measurements are used to get an understanding of the control allocation and to model the static forces and moments acting on the system. Based on the derived model, a novel controller that operates in SO(3) and handles the dynamics of the vehicle at any attitude configuration, including the rotorcraft and fixed-wing regimes as well as their transitions, is presented. This unified controller allows the autonomous transition of the system without discontinuities of switching, as well as its overall high performance flight control. The capabilities and flying qualities of the platform and the controller are demonstrated and evaluated by means of extensive experimental studies.