With the rapid development of 6G space–air–ground integrated communication networks, low Earth orbit (LEO) satellite constellations, leveraging their advantages of wide-area coverage and freedom from geographic constraints, have become key infrastructure for achieving global seamless connectivity. However, due to the relative motion among satellites in different orbits, inter-satellite links (ISLs) exhibit periodic dynamic on–off characteristics, among which a portion of the interruptions are predictable topological changes. Conventional Open Shortest Path First (OSPF) protocols compute shortest paths solely based on link distance, without considering link effective duration or bandwidth constraints, rendering them inadequate for adapting to the dynamic topological characteristics of satellite networks. Although fast reroute strategies can address sudden link failures, they consume substantial bandwidth resources and cannot provide protection for all nodes across the entire network. Therefore, how to proactively switch service paths before predictable link interruptions occur, so as to minimize service disruption and resource overhead, has become a core issue in ensuring service continuity in LEO satellite networks.

The near-Earth asteroid Apophis will make an extremely close flyby of Earth on April 13, 2029, at a distance of approximately 38,000 km—an event that occurs on average only once every 7,500 years, offering an unprecedented opportunity for planetary science and planetary defense. However, significant uncertainties remain regarding the physical parameters of Apophis, such as its shape, spin state, internal structure, and material composition, and predictions of tidal effects—including potential orbital changes, spin acceleration, surface material displacement, and dust ejection during the flyby—are highly dependent on model assumptions. Although multiple nations have planned exploration missions, how to coordinate global observational resources within the limited time window, optimize rapid-response mission architectures, and translate scientific understanding into effective planetary defense strategies remain critical challenges to be addressed.

With the long-term on-orbit operation of space stations, extravehicular status monitoring and surface inspection tasks have imposed higher demands on the motion planning capabilities of manipulators. Space redundant manipulators, when performing visual monitoring tasks, must simultaneously satisfy multiple complex constraints including kinematics, dynamics, obstacle avoidance, and end-effector line-of-sight, making this a typical nonlinear non-convex optimal control problem. Although sampling-based methods can rapidly generate collision-free paths, they struggle to guarantee dynamic feasibility in high-dimensional systems and often yield poor-quality paths. Optimization-based methods, while capable of directly generating high-quality trajectories, are highly sensitive to initial solutions and lack effective warm-start mechanisms. Therefore, how to merge the rapid search capability of sampling-based methods with the precise solving advantage of optimization-based methods to plan high-quality executable trajectories under complex constraints for space manipulators has become a key challenge in advancing the intelligent development of space robotics.

The near-Earth asteroid Apophis will make an extremely close flyby of Earth on April 13, 2029, at a distance of approximately 38,000 km—an event that occurs on average only once every 7,500 years, offering an unprecedented opportunity for planetary science and planetary defense. However, significant uncertainties remain regarding the physical parameters of Apophis, such as its shape, spin state, internal structure, and material composition, and predictions of tidal effects—including potential orbital changes, spin acceleration, surface material displacement, and dust ejection during the flyby—are highly dependent on model assumptions. Although multiple nations have planned exploration missions, how to coordinate global observational resources within the limited time window, optimize rapid-response mission architectures, and translate scientific understanding into effective planetary defense strategies remain critical challenges to be addressed.

With the intensifying space confrontation in geostationary orbit (GEO), the U.S. GSSAP (Geosynchronous Space Situational Awareness Program) satellites have conducted hundreds of close-range observation operations on dozens of on-orbit satellites in the vicinity of GEO. The acquisition of multi-aspect information from non-cooperative targets has thus become a critical component of space security assessment. Close-range spacecraft operations, which employ relative motion configurations such as fly-around, hovering, and drifting flight, provide an effective technical means for approaching and observing targets to obtain multi-aspect payload information. However, existing studies predominantly focus on the control design of a single relative motion configuration, which fails to satisfy the complex mission requirements of multi-aspect observation. The combination of multiple models for observation presents multiple challenges, including smooth switching between modes, fuel optimization, strategy design algorithms, and analysis of payload parameter effects. Therefore, how to coordinately plan a sequential combination of multiple close-range operation models under minimum fuel constraints to efficiently acquire multi-aspect information of non-cooperative targets has become a key bottleneck in enhancing space situational awareness capabilities.