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
1983368461
This paper presents modelling, simulation and implementation of a quadrotor Unmanned Ariel Vehicle (UAV) Focus of this work is to gain in-depth understanding of quadrotor dynamics to develop a simulator and a laboratory platform to facilitate future development of control algorithms, automatic navigation systems, and trajectory planning for quadrotors. Quadrotor dynamics is modeled using Newton-Euler method. The model predicts the effects of the forces and torques generated by the four propellers on the quadrotor motion. Based on the model, a quadrotor simulator was developed in MATLAB® Simulink, on which various control algorithms can be developed and tested. A quadrotor prototype was built on which some of the control algorithms were tested experimentally in different environments to evaluate the stability and controllability of the platform. Experimental flight data and simulation results were compared to validate the accuracy of the dynamic model.