Failure detection of Unmanned Aerial Vehicle (UAV) motors and propulsion systems is the most important step in the implementation of active fault-tolerant control systems. This will increase the reliability of unmanned systems and increase the level of safety, especially in civil and commercial applications. The following paper presents a method of motor failure detection in the multirotor UAV using piezo bars. The results of a real flight, in which the failure of the propulsion system caused the crash of a hybrid VTOL UAV, were presented and analyzed. The conclusions drawn from this flight led to the development of a lightweight, simple and reliable sensor that can detect a failure of the UAV propulsion system. The article presents the outcomes of laboratory tests concerning measurements made with a piezo sensor. An extensive analysis of the obtained results of vibrations recorded on a flying platform arm with a propulsion system is presented, and a methodology for using this type of data to detect failures is proposed. The article presents the possibility of using a piezoelectric sensor to record vibrations on the basis of which it is possible to detect a failure of the UAV propulsion system.

Concept of the magnetic launcher for medium class unmanned aerial vehicles designed on the basis of numerical calculations

One of the issues related to formation flights, which requires to be still discussed, is the stability of formation flight in turns, where the aerodynamic conditions can be substantially different for outer vehicles due to varying bank angles. Therefore, this paper proposes a decentralized control algorithm based on a leader as the reference point for followers, i.e. other UAVs and two flocking behaviors responsible for local position control, i.e. cohesion and repulsion. But opposite to other research in this area, the structure of the formation becomes flexible (structure is being reshaped and bent according to actual turn radius of the leader. During turns the structure is bent basing on concentred circles with different radiuses corresponding to relative locations of vehicles in the structure. Simultaneously, UAVs' air-speeds must be modified according to the length of turn radius to achieve the stability of the structure. The effectiveness of the algorithm is verified by the results of simulated flights of five UAVs.

A problem of unmanned aerial vehicles (UAVs) being able to avoid obstacles and collisions by means of processing the images taken by one camera is presented in the paper. The optical flow method based on gradient method of Lukas-Kanade was used to obtain the tested structure in 3D space environment (extraction of image's depth). This method allows to generate local information flow patterns from particular neighborhood of surrounding points. Presented algorithm for obstacle location and estimation of its shape was developed and implemented on the workstation with real time uClinux system. Proposed vision-based obstacle avoidance algorithm is demonstrated in simulation and in hardware in the loop flight tests on a fixed-wing UAV.