Abstract: A guidance method based on Markov decision is designed to effectively improve the accuracy of automatic landing, in response to the problem of significant deviation when using only civilian GPS guidance for automatic landing of quad-rotor helicopter.First, an alignment method based on the improved artificial potential field algorithm is designed. The AprilTag3 recognition algorithm is used to quickly identify the landing tag and build the potential field at its center. The yaw alignment of aircraft and pitch alignment of gimbal are performed under the gravitational pull. Secondly, the landing process is established as a time-aligned Markov Decision Process model. The state transition relationship among the action set, state set and reward set is designed to prevent the aircraft from deviating from the expected state. Finally, combined with the environment of automatic landing, an information set is added on the basis of the MDP model.The information during flight is used to assist in the determination of the transfer relationship in order to improve the accuracy of states and actions’ decision-making. Actual flight verification was carried out on the ANAFI quad-rotor helicopter platform. The experimental results showed that the automatic landing guidance method based on the MDP model can effectively suppress excessive movements and misjudgments of the aircraft during the landing process. The landing error has been reduced from the meter level to about 10 centimeters, meeting the accuracy requirements for automatic landing of quad-rotor helicopters.

Key words: Markov process, Automatic landing, Data fusion, Artificial potential field, Quad-rotor helicopter