A Dynamic Path Planning Method for Spacecraft Cluster

Abstract

The invention provides a dynamic path planning method for a spacecraft cluster. Since the orbital dynamics equation in the three-dimensional space is highly nonlinear, the modeling is carried out in consideration of the space force that the spacecraft is subjected to in space, and the collaborative particle swarm algorithm is used to achieve the modeling. The autonomous search process of the path planning of the spacecraft cluster can perfectly complete the path planning of the spacecraft cluster with optimal fuel as the optimization index under the conditions of considering the space obstacles and the internal constraints of the spacecraft cluster. This method performs dynamic path planning under the premise of considering obstacles in three-dimensional space, and obtains the optimal path under the premise of avoiding obstacles.

Description

technical field [0001] The invention belongs to the field of spacecraft cluster dynamic path planning, in particular to a spacecraft cluster dynamic path planning method. Background technique [0002] In recent years, the spacecraft swarm system has become a research hotspot in the aerospace field. Although the spacecraft swarm has only just emerged in the aerospace field, referring to its development in the aviation field or in ground missions, it can be seen that the use of intelligent spacecraft swarms to perform space missions has a huge impact. Prospective, such as: using multiple spacecraft to perform observation, round-up, transportation, or repair tasks on close-range targets; using multiple spacecraft to form temporary relay communication satellites; or using multiple spacecraft to verify aggregation, docking, or separation technology, etc. [0003] The path planning problem of spacecraft swarms is a key problem in the research of spacecraft swarms. Huang Haibin p...

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Problems solved by technology

Huang Haibin proposed a method of using particle swarm optimization algorithm to design spacecraft cluster paths in the document "Research on Autonomous Formation Reconstruction Method for Satellite Formation Flight", but it did not consider possible environmental obstacles; Zhang Bin in the document " In "Study on Hunting Behavior of Swarm Robots Based on Particle Swarm Algorithm", particle swarm algorithm and artificial potential field method were used to plan and design the robot path in two-dimensional environment, but it did not consider the situation in three-dimensional environment; Xie Jing wrote in "Confrontation In "Research on Multi-robot Group Game and Coordinated Control in the Environment", the path planning and design of the UAV swarm was carried out in the three-dimensional environment. There is a significant difference in the force on the machine

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