Abstract:

This paper presents an on-line trajectory planning method based on the reinforcement learning for driving the quadrotor to its destination accurately and suppressing the swing motion of the slung-payload effectively. To deal with the unknown external disturbances, the desired trajectory of the Unmanned Aerial Vehicle (UAV) is divided into two parts: the positioning trajectory planning and the disturbance rejection trajectory planning. The positioning trajectory planning can be designed in advance to guide the UAV to reach the desired position, and the disturbance rejection trajectory planning can compensate the unknown external disturbances based on the reinforcement learning strategy and suppress the swing motion of the slung-payload simultenously. The Lyapunov based stability analysis is employed to prove the stability of the closed-loop system, the convergence of the UAV′s position and the swing motion of the slung-payload. Finally, real-time comparing experiments are performed to verify the effectiveness of the proposed trajectory generation method and its robustness to external disturbances and variation of the mass of the slung-payload.

Key words: automatic control technology, quadrotor unmanned aerial vehicle, slung-payload system, reinforcement learning, trajectory planning