Python Library for simulating unManNed vehiclEs(PLANE) is an open source software module, written in Python, that focuses on Unmanned Aerial Vehicles (UAVs), on their movements and on the mechanics of flight, thus devoting particular attention to the equations that describe drones' movement. In the context of the Internet of Drones (IoD), the module can be widely used for the study of the mutual control of position coordination in scenarios in which drones may find obstacles, as it happens in densely populated urban scenarios. Emphasis is put on ease of use, performance evaluation, documentation, and Application Programming Interface (API) consistency. The software tool has minimal dependencies and is distributed under MIT License. Source code, binaries, and documentation can be downloaded from GitHub.
In @cite_14 it is proposed the implementation of a 4-rotor control system Note that it does not fit all real drones, as a number of them are based on six-rotors. solution, verified using MATLAB Simulink. It is worth remarking that these studies are specifically designed for 4-rotors systems.
@cite_14
2149067903 2172041073 2109656638 2579730571
An original configuration of a small aerial vehicle having eight rotors is presented. Four rotors are devoted to the stabilization of the orientation of the helicopter, and the other four are used to drive the lateral displacements. A precompensation on the roll and pitch angles has been introduced so that the attitude dynamics is practically independent of the translational dynamics. This compensation is directly related to the velocity of the lateral motors. The dynamical model is obtained using the Euler-Lagrange approach. The proposed configuration is particularly useful for image processing since the the camera orientation is held constant. The eight-rotor rotorcraft is simpler to pilot than other rotorcrafts. A control strategy is proposed that uses the optical flow measurements to achieve a hover flight that is robust with respect to perturbations like wind. The new aerial configuration and control strategy have been tested in real-time experiments. In this paper we present an overview of techniques and approaches used for a load transportation system based on small size unmanned helicopters. The focus is on the control approach and on the movement of the rope connecting helicopters and load. The proposed approach is based on two control loops: an outer loop to control the translation of each helicopter in compound and an inner loop to control the orientation of helicopters. The challenge here is that in both loops the dynamics of the whole system - all helicopters and load - should be accounted for. It is shown, that for designing the outer loop controller a complex model of the helicopters and load can be replaced by a simplified model based on interconnected mass points. For designing the inner loop controller, the complete dynamics of the whole system are considered. The usage of force sensors in the ropes is proposed in order to simplify the inner loop controller and to make it robust against variations of system parameters. The presented inner loop controller is independent of the number of coupled helicopters. The outer loop controller depends on the number of helicopters. The problem of oscillations in the flexible ropes due to external disturbancies (e.g. wind gusts) is discussed and a solution based on load state observer is presented. The performance of the presented system was verified in simulations and in real flight experiments with one and three helicopters transporting the load. The worldwide first demonstration of a slung load transportation using three helicopters was performed in December 2007. This paper provides new results for the tracking control of a quadrotor unmanned aerial vehicle (UAV). The UAV has four input degrees of freedom, namely the magnitudes of the four rotor thrusts, that are used to control the six translational and rotational degrees of freedom, and to achieve asymptotic tracking of four outputs, namely, three position variables for the vehicle center of mass and the direction of one vehicle body-fixed axis. A globally defined model of the quadrotor UAV rigid body dynamics is introduced as a basis for the analysis. A nonlinear tracking controller is developed on the special Euclidean group SE(3) and it is shown to have desirable closed loop properties that are almost global. Several numerical examples, including an example in which the quadrotor recovers from being initially upside down, illustrate the versatility of the controller. This paper presents a novel control algorithm to regulate the aerodynamic thrust produced by fixed-pitch rotors commonly used on small-scale electrically powered multirotor aerial vehicles. The proposed controller significantly improves the disturbance rejection and gust tolerance of rotor thrust control compared to state-of-the-art RPM (revolutions per minute) rotor control schemes. The thrust modeling approach taken is based on a model of aerodynamic power generated by a fixed-pitch rotor and computed in real time on the embedded electronic speed controllers using measurements of electrical power and rotor angular velocity. Static and dynamic flight tests were carried out in downdrafts and updrafts of varying strengths to quantify the resulting improvement in maintaining a desired thrust setpoint. The performance of the proposed approach in flight conditions is demonstrated by a path tracking experiment, where a quadrotor was flown through an artificial wind gust and the trajectory tracking error was measured. The proposed approach for thrust control demonstrably reduced the tracking error compared to classical RPM rotor control.