Coaxial quadcopter trajectory optimization and control

Coaxial quadcopter trajectory optimization and control The use of mobile robots is growing exponentially in civil and industrial application, using technologies like GPS and Lidar to guarantee an accurate localization of the robot and a precise environment mapping. However, there are many situations in which such solutions are impossible to adopt due to physical or technological limitations (e.g., the GPS is impossible to use in indoor environments or in place in which the satellite coverage is not guaranteed). This thesis aims to design a possible trajectory planning of a drone without using the GPS signal and the Lidar, traditionally adopted elements in drone operations. This solution is applied in the framework of the motion planning of the coaxial quadcopter designed by the DRAFT Polito of Politecnico di Torino for the Leonardo Drone Contest launched by Leonardo, in which the objective is to navigate in an unknown environment without the adoption of a GPS signal and a Lidar sensor. The drone uses for its navigation only visual and inertial sensors, and its software is internally based on ROS (Robotic Operating System). To achieve this result, the motion planning is divided into two separate parts: a global path planning, using the search algorithm A* and a local path planning that adopts the Dynamic-Window-Approach (DWA) in order to take into account the presence of uninspected obstacles. To obtain better performances in terms of mission duration and electrical consumption during the flight, a genetic algorithm with fuzzy aggregation is applied to evaluate the best solution that satisfies both the conflicting requests. Successively, the solution is tested in a simulation environment, and it can be a starting point for future improvements.