This repository contains the final project for the Field and Service Robotics exam. The work is divided into two main phases:
- Analysis of the quadcopter system, focusing on its characteristics such as controllability and underactuation.
- Application to a chosen scenario—in this case, a military context involving multiple obstacles that must be avoided to reach a target destination. Various motion planning strategies and one control strategy (selected from those studied) are implemented using MATLAB/Simulink.
The files included in this repository are:
- MAIN.m – this is the main file that the user must run; it links all the other files.
- environment_definition.m – defines the map.
- rrt_motion_planning.m – given an initial pose, a final pose, and a maximum number of iterations, it implements the RRT algorithm to find a path (i.e., a set of collision-free waypoints) from the initial to the final position.
- rrtstar_motion_planning.m – implements the optimal version of RRT.
- inf_rrtstar_motion_planning.m – implements the informed version of RRT*.
- passivity_based_controller.slx – contains the control scheme implementing the controller.
Standard RRT Algorithm
RRT* Algorithm
Informed RRT*
Block diagram showing the generation of the reference trajectory.
Control architecture based on passivity principles.
This animation shows the final result produced by the UAV Toolbox block in the Simulink scheme.
[1] J.D. Gammell, S.S. Srinivasa, and T.D. Barfoot “Informed RRT*: Optimal Sampling-based Path Planning Focused via Direct Sampling of an Admissible Ellipsoidal Heuristic”.
[2] F. Ruggiero, J.Cacace, H.Sadeghian, V. Lippiello “Passivity-based control of VToL UAVs with a momentum-based estimator of external wrench and unmodeled dynamics”.