Pose control of quadrotor unmanned aerial vehicle based on double filters

Abstract

In recent years, the quadrotor unmanned aerial vehicle(UAV) showed a huge advantage in disaster relief activities due to its maneuverability and flexibility. However, the scene of the indoor environment is usually complex and difficult to be detected, the pose control and autonomous navigation for unmanned aerial vehicle meets great difficulties. For the pose control of the quadrobot unmanned aerial vehicle in unknown indoor environment, this paper designed a complementary filter and the Kalman filter. Based on the state estimation by iterations, we effectively implemented the fusion of the close-loop control process and the multi-sensor measurement data. This greatly improves the real-time performance and precision of the pose control for quadrobot UAV. Simulation experiments show that the pose control system designed in this paper can achieve excellent effect when it was applied for autonomous flight of quadrobot UAV. This laid a solid foundation for the navigation of unmanned aerial vehicle.