Satellite mission planning is the basis and top-level work of space missions and the beginning of each space mission. Therefore, the scientific research of satellite mission planning is very important. By analyzing the existing research results, we can know that the research on task planning mainly focuses on three aspects: research objects, established model, and solution algorithm. Starting from these three aspects vertically and then horizontally, this paper comprehensively discusses the theoretical basis, application, and advantages and disadvantages of related technologies in the research literature in recent years. Finally, based on the research on satellite mission planning, this paper puts forward its own views on the future development direction and research focus.

This paper investigates the application of particle swarm optimization (PSO) algorithm to plan joint trajectories of the space modular reconfigurable satellite (SMRS). SMRS changes its configuration by joint motions to complete various space missions; its movement stability is affected by joints motions because of the dynamic coupling effect in space. To improve the movement stability in reconfiguration progress, this paper establishes the optimization object equation to characterize the movement stability of SMRS in its reconfiguration process. The velocity-level and position-level kinematic models based on the proposed virtual joint coordinate system of SMRS are derived. The virtual joint coordinate system solves the problem of asymmetric joint coordinate system resulted by the asymmetric joint arrangement of SMRS. The six-order and seven-order polynomial curves are chosen to parameterize the joint trajectories and ensure the continuous position, velocity, and acceleration of joint motions. Finally, PSO algorithm is used to optimize the trajectory parameters in two cases. Consistent optimization results in terms of the six-order and seven-order polynomial in both cases prove the PSO algorithm can be effectively used for joint trajectory planning of SMRS.

Space modular self-reconfigurable satellite (SMSRS) is a new type of satellite. The research on self-collision avoidance of SMSRS is important for its on-orbit safety but is not completely solved. This paper offers a new method for joint path planning for self-collision avoidance of SMSRS. Firstly, we establish the collision detection model for SMSRS based on forward kinematics and the spherical nonholonomic envelope to detect the collision occurring in SMSRS. Then, to achieve offline path planning in joint space, we proposed the self-collision avoidance strategy, which splices multiple C-spaces based on the pre-defined joint path into a binary map, and then transforms the binary map into a map with the dangerous potential field, and planning algorithms based on a map with the dangerous potential field is proposed to find the optimal collision-free path. The new method is applied to two cases and both find collision-free joint paths for SMSRS successfully, which demonstrates the feasibility of the method. In addition, this study bridges the gap in the study of self-collision avoidance of super-redundant self-reconfigurable satellites.

The extent of the impact of mega constellations on the low-orbiting geospace environment, which has not yet been assessed in more concrete quantitative terms, is an extremely important issue to consider as mega constellations are built. Satellite safety and lifetime can clearly represent the situation of space targets, and thus can reflect the impact of mega constellations on geospace security. Three target satellites with different characteristics were selected and the Accepted Collision Probability Level (ACPL) was calculated to obtain the impact of Starlink on satellite mission lifetime. Upon considering Starlink without early avoidance control, the lifetimes of the three target satellites were shortened by 56.21%, 99.09%, and 99.82%, respectively. After 10 revolutions of early avoidance control, two were shortened to 92.166% and 91.99%, while the lifetime of JILIN-01 was extended by 155.44%. After joining Starlink, the total risk became larger; even if the target satellite avoided control far more frequently than before joining Starlink, it will face a worse geospace environment. Adopting the most aggressive orbit avoidance control cannot avoid the deterioration of the geospace environment from the perspective of satellite lifetime, which is an irreversible and deteriorating process.

Space modular self-reconfigurable satellites (SMSRSs) are a new type of satellite with reconfigurable structures and adjustable functions. The inverse kinematics of the hyper-redundant structure of SMSRSs are difficult to solve by traditional methods. In this paper, the inverse kinematics of SMSRS is transformed into an optimization problem and solved using the optimization method. Moreover, the avoidance of self-collision is implemented in the optimization process. Firstly, the kinematic model of SMSRS is established. Then, to find the more accurate inverse kinematics solutions, a novel Segmented Hybrid CMA-ES and PSO (SHCP) algorithm is proposed. The algorithm is used for three cases of inverse kinematic problems, and the optimization results prove the optimization method is effective to solve the inverse kinematic problem with self-collision avoidance. Compared to the results of PSO variants, meta-heuristic algorithms, and hybrid algorithms, the novel algorithm has higher accuracy, proving its better performance on the inverse kinematics problem of SMSRS.