Improved Artificial Field Method Based on the Flight Situation Awareness Map in Coaxial Rotor UAV

The use of unmanned aerial vehicle (UAV) has been recognized by the majority of people, and is regarded as a reliable tool to complete some tasks. As for the obstacle avoidance of coaxial rotor UAV (CR-UAV), a flight pattern map (Flight Situation Awareness Map: FSAM) that can sense the flight environment and an integrated control method (Improved Artificial Potential Field: IAPF) based on the common artificial potential field method with appropriate improvements to achieve obstacle avoidance (IAPF). Firstly, we construct the FSAM, which can map the environment information around the UAV on the FSAM. Then, based on the FSAM, the IAPF functions are established to achieve the obstacles avoidance. Cause the artificial potential field (APF) has a characteristic that cannot avoid: the problem of local minima, a rotating potential field is put forward to ensure that the CR-UAV has only one potential equilibrium point at the target point in the environment, and it will improve the ability of CR-UAV to avoid complex obstacles. At the end of this study, through data analysis, the performance of obstacle avoidance and the attitude stability of CR-UAV are good, the simulation results confirm that the approaches proposed in this paper can address the obstacles avoidance successfully.