Absolute ages provide vital information in establishing the geological history of the Solar System’s solid bodies. For extraterrestrial bodies, only the Moon has been sampled in a few areas for radiometric dating in the laboratory. For the unsampled areas on the Moon, the widely used surface dating method is based on the crater size–frequency distribution (CSFD) technique. However, there are no returned Martian samples, so the above method cannot be directly applied for Mars. The Martian isochrons have usually been derived based on the production function (PF) and chronology function (CF) of the Moon. Many uncertainties cast a shadow on the reliability of the current Martian isochrons (e.g., the maximum age difference is up to ~1.0 Ga from meteor flux ratios of 2.04 and 3.0). Thus, obtaining the Martian crater PF directly from remote sensing observations is a necessary and significant task. 

Relevant technological advancements in recent years have established solar sailing as an attractive propulsion system for terrestrial and interplanetary space missions, particularly missions that require low-thrust propulsion for long periods of time. The initial stages in designing solar sail missions involve a thorough analysis of possible transfer trajectories. Traditional approaches primarily focus on deterministic scenarios where the spacecraft dynamics is precisely defined and fully characterized. Whereas, space trajectories are inevitably subject to various sources of uncertainty, including modeling errors in the dynamics, inaccurate measurements, and unpredictable environmental effects, such as fluctuations in solar irradiance. These uncertainties necessitate the development of robust control strategies that can effectively handle stochastic effects. In recent years, reinforcement learning (RL) offers a promising framework for addressing optimization problems characterized by significant uncertainty, which can be challenging to handle using traditional methods. Meanwhile, deep reinforcement learning (DRL) utilizes neural networks (NNs) to approximate complex policies, i.e. control laws. 

Einstein’s general theory of relativity reveals that spacetime can be warped by mass and energy. As a conjecture in this context, the evolution of space-time curvature affected by gravitation will propagate through the vast universe like ripples. There remains a wealth of mysteries about astrophysics that have not been explored yet, and these “ripples” called gravitational waves may revolutionize the investigation for this. Space-based gravitational-wave observations, which broadly adopt heliocentric, geocentric, or libration-point architectures, can extend the scope to celestial bodies that generate valuable millihertz frequency waves and escape the Earth-bound noise. The heliocentric gravitational-wave detection relying on laser interferometry faces dual challenges: 1) the attitude errors couple into the interferometric arm-length measurements, potentially corrupting the picometer-level displacement sensitivity, making the attitude accuracy exceptionally rigorous, while 2) the ultra-long interferometric arms (and thus million-kilometer-scale intersatellite communication distances) introduce significant communication delays. As a key to space-based gravitational-wave observations, the past few years have witnessed the development of attitude-orbit control technique, and numerous control methodologies have sprung up for various space missions. However, current communication delay models and their corresponding compensation methods prove inadequate for heliocentric gravitational-wave detection scenarios. Additionally, in line with adaptive SMC, there are few investigations on attitude-orbit coordinated control for heliocentric gravitational-wave detection spacecraft formation. 

As we venture deeper into space and establish bases and orbital stations on celestial bodies, it is imperative to develop sustainable space transportation methods that minimise propellant usage. Currently, the most common method for Earth-Mars transfers is through chemical propulsion systems. While the chemical propulsion system is well established, it has several drawbacks, including low efficiency, high propellant mass requirements, thermal limitations, and operational complexity. Momentum exchange tethers, which, in theory, can operate without the need for any propellant, offer an innovative alternative to these propulsion systems. Especially, in a symmetrical tether, the COM lies at the centre of the length. If both the equal mass payloads are released at the same time, then the orbit of the tether does not change. Additional delta-v can be generated by the libration (oscillation) or rotation of the tethers, which can be induced by a motor facility. Though there are various investigations into space tethers, there is a gap in the use of symmetrical tethers for interplanetary transfers. 

Sudden surface anomalies (SSAs)—ranging from earthquakes and floods to wildfires and industrial accidents—pose escalating threats to ecosystems and societies worldwide. With its advantages of wide coverage, high revisit frequency, and rich information content, remote sensing is regarded as an effective tool for rapid detection and early warning of such anomalies. However, significant technical bottlenecks remain in using remote sensing to monitor SSAs, such as delays due to revisit intervals and complex data processing chains and challenges for the integration and joint analysis of multi-source information, resulting in frequent occurrences of missed detections and false alarms. Real-time remote sensing has emerged as a transformative approach for monitoring and early warning of such abrupt events, driven by recent advances in satellite constellations, on-orbit artificial intelligence, and multi-source data fusion.