Trajectory planning of stratospheric airship for station-keeping mission based on improved rapidly exploring random tree

Abstract

The station-keeping mission is one of the common missions of stratospheric airships. Its movement is sensitive to wind due to the large size and low airspeed of stratospheric airships. When the wind speed exceeds the maximum airspeed of the airship, the airship may fly out of the given mission region. Therefore, station-keeping trajectory planning is a new trajectory planning problem that has never existed before. A rapidly exploring random tree algorithm for station-keeping(RRT-SK) is proposed to solve the trajectory planning problem under multiple constraints of the airship, and an artificial potential field method (APF) considering wind field and relative position is designed as the objective function of the RRT-SK algorithm, both of which form the RRT-SK strategy used for the stratospheric airship station-keeping trajectory planning under multiple constraints. A multidisciplinary model is developed to simulate multiple constraints on the airship flight, including the energy model, thermal model, propulsion model, and kinematic model. The performance of the RRT-SK strategy is demonstrated in this multidisciplinary model with real wind fields. The results show that the multi-constrained station-keeping problem can be solved by the RRT-SK strategy. Compared with the conventional strategy, the RRT-SK strategy can improve the success rate of the airship’s 24-h stationing flight and well cope with the impact of wind field changes and stationing area changes. Moreover, the RRT-SK strategy has better advantages in actual long-duration use.