PRM navigation in trading drone and Gazebo simulation

Abstract

Starting from a commercial drone AR Dron Parrot 2.0, an autonomous navigation process is developed with a PRM probabilistic route planner in real time, through a ROS network between the drone and the Gazebo simulation software. Using the robotics system toolbox from software Matlab that interacts with Gazebo, it is possible to study the desired trajectory planner, in addition, the creation and connection of the ROS network on the Linux operating system, where the navigation algorithm is analyzed from the practical vs., simulation points of views. The errors that are presented are minimal, taking into account the propagation delays and the control algorithm; this is in charge of receiving location information in order to correct and minimized the mean square error.

Keywords

• drone
• gazebo
• matlab
• navigation
• prm
• ros