DroneSimulator
Application to simulate the execution of trajectories in aerial drones. Designed and developed to be multiplatform (GNU / Linux, Mac OS X and Windows), fully programmed in C ++ language with a graphic interface in OpenGL. It incorporates complete mathematical models of the drone in the simulation, where the input variables are the speeds of the motors and the output variables are the state of position and orientation of the drone. The control of the position and orientation can be executed with PID and / or fuzzy controllers, in addition to including different saturations to ensure the precise values of the variables. It contains a compilation of several trajectories for the tests, and different disturbances of wind and noise in the sensors to resemble a real behavior. The drone model data is based on the AR.Drone 2.0 device from Parrot. The application allows a real implementation with this robotic platform. The communication uses the ROS libraries in conjunction with the 'ardrone_autonomy' package. The estimation of position and orientation is obtained by mixing the odometry of the 'ardrone_autonomy' package with an external reference provided by the 'ar_track_alvar' package from the main camera.
Install / Use
/learn @ricardol8a/DroneSimulatorREADME
DroneSimulator
Application to simulate the execution of trajectories in aerial drones. Designed and developed to be multiplatform (GNU / Linux, Mac OS X and Windows), fully programmed in C ++ language with a graphic interface in OpenGL. It incorporates complete mathematical models of the drone in the simulation, where the input variables are the speeds of the motors and the output variables are the state of position and orientation of the drone. The control of the position and orientation can be executed with PID and / or fuzzy controllers, in addition to including different saturations to ensure the precise values of the variables. It contains a compilation of several trajectories for the tests, and different disturbances of wind and noise in the sensors to resemble a real behavior. The drone model data is based on the AR.Drone 2.0 device from Parrot. The application allows a real implementation with this robotic platform. The communication uses the ROS libraries in conjunction with the 'ardrone_autonomy' package. The estimation of position and orientation is obtained by mixing the odometry of the 'ardrone_autonomy' package with an external reference provided by the 'ar_track_alvar' package from the main camera.
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