Abstract
The trajectory planning of spacecraft near-distance motion is a core technology of spacecraft's autonomous orbit service, its difficulty lies in its autonomy and real-time. Aiming at the trajectory planning of the small thrust spacecraft tracking the non -cooperative target, the autonomous trajectory planning of the spacecraft can be realized by using the sampling planning method.
According to the order of the basic algorithm and the practical application, this paper studies the trajectory planning problem of the orbit service spacecraft for the impulse thrust and the continuous thrust respectively. Mainly includes the following research content:
Firstly, the classical rapidly-exploring Random tree* (RRT*) algorithm has been introduced briefly, and its limitations have been analyzed. On this basis, through the improvement of the original algorithm in search mode, sampling strategy, measurement function and cost function, an improved RRT* algorithm with higher computational efficiency and better optimization has been presented, and the probability completeness, fast convergence and asymptotic optimality of the improved RRT* algorithm have been proved.
Secondly, according to the trajectory planning problem of the spacecraft with small pulse thrust, the coplanar trajectory planning environment model is established through two kinds of different obstacle distributions. The simulation experiment of the RRT, RRT* and the improved RRT* algorithm has been carried out through the establishment of two two-dimensional programming environment model with different distribution of obstacles, and the improvement RRT* The algorithm can be applied to the trajectory planning problem of the orbit service spacecraft based on the pulse small thrust mode, and the basic properties of the RRT* have been improved.
Finally, the improved RRT* algorithm cannot realize the asymptotic optimization problem of trajectory planning of the orbit service spacecraft based on the continuous small thrust mode, and improves the RRT* by simplifying the steer function, selecting the best selection point and pruning based on the local optimization of the new node.
II
The trajectory planning of the spacecraft with dynamic constraints has been realized. In this paper, a RRT* trajectory planning method based on rolling time domain has been also presented to deal with the occurrence of unknown obstacles or other unexpected events. Finally, the applicability of the new improved RRT* algorithm to the spacecraft trajectory planning problem of the continuous thrust model has been validated by the comparison experiment between the RRT* algorithm and the newly improved RRT* algorithm.
Keywords：On-orbit service; Trajectory planning; Sampling planning; RRT* algorithm
III