3D path planning of UAV using model predictive control

Abstract

Path planning is essential for UAVs that travel in different terrains. Designing feasible path planners for UAVs taking the dynamic constraints is difficult. In this thesis, we develop a 3D path planner using model predictive control (MPC) methods for a quadrotor. The MPC based controller optimizes the control effort required to travel a given reference path. The obtained path avoids infeasible regions of the terrain and also threats. The MPC takes constraints on jerks, position and angular acceleration on the quadcopter. Simulation results are presented to validate our approach.