Fixed-wing UAV motion planning and optimal control for curve tracking
Leonardo A. A. Pereira · 2021
As the use of unmanned aerial vehicles (UAVs) is increasing, new techniques for motion planning, navigation and control are being developed. Both military and civilian applications usually require a UAV to be able to estimate its own pose, process the information provided by the environment, and follow a given trajectory autonomously. Besides, some tasks such as surveillance, terrain mapping and convoy protection require long endurance. For those tasks, the use of a fixed-wing UAV is highly recommended due to its greater endurance when compared to rotary-wing UAVs. This work presents a strategy for solving the problem of guiding and controlling a UAV to follow a closed curve while avoiding dynamic obstacles. The proposed strategy can be divided into two parts. In a top layer, a vector field strategy is used which alternates between two forms: a vector field to converge to and circulate the target curve, and one to avoid obstacles along the UAV path. For a lower layer, a feedback linearization controller is proposed, in which a linear Model Predictive Control (MPC) is used as the auxiliary control law to make the UAV follow the references provided by the vector fields. Simulations using Matlab and the entire UAV model, with 6 degrees of freedom and 12 states, demonstrate the efficiency of the proposed strategy for different scenarios. Results obtained using an embedded computational system demonstrate that the proposed strategy is feasible to be implemented on a physical platform.