The exploration of ice giant systems represents one of the priority areas in deep space exploration for the coming decade. Owing to the vast orbital distances of these planets and the need for extensive in-system transfers during missions, trajectory design and optimization constitute a critical enabling technology for the exploration of ice giant systems. While numerous mission concepts and orbital design methodologies have been proposed to date, a comprehensive review of these methodologies is currently lacking, which hinders the further development of novel design techniques and the formulation of new mission proposals. This survey systematically synthesizes both established and state-of-the-art methods across four primary mission phases: interplanetary transfer, ice giant capture, planetary satellite tours, and other scientific observations targeting planets and comets. For each phase, different design strategies are introduced, with their advantages and capabilities described and analyzed to reveal technological progress. Finally, perspectives on future developments are provided, aiming to establish a reference framework for further research in trajectory design and optimization for ice giant system exploration.

This paper presents a fuel-saving Jovian capture approach utilizing solar gravity perturbation (SGP). A scheme of utilizing SGP with prograde arrivals is proposed, enabling the combination of SGP utilization with multiple-moon-aided Jovian capture. To efficiently utilize SGP, the effects of SGP on the change in the perijove are analyzed via parametric study in the Sun–Jupiter circular restricted 3-body problem. Thereafter, the mechanism of utilizing SGP with respect to the phase angle of the perijove, the perijove radius, and the eccentricity of the capture orbit is concluded. The best condition of SGP utilization and the characteristics of the required flight time are also revealed. Finally, moon-aided capture trajectories utilizing SGP are designed in both simplified and high-fidelity dynamical models. The simulation results indicate that the proposed method can reduce the velocity increment substantially.

This paper presents the results and design methods of team Nanjing University of Aeronautics and Astronautics in the 12th edition of the Global Trajectory Optimization Competition. To address the problem of sustainable asteroid mining, we focus on the following: analyzing the constraints and asteroids involved; selecting a candidate set of asteroids for which mining missions can be performed easily; establishing an algorithmic flow using phasing indicators, multiobjective beam search, and a genetic algorithm to determine the sequence of asteroid visits for mining ships; and optimizing low-thrust trajectories via an indirect method and global optimization. In addition, a central-node method is proposed to simplify the design process and reduce the computational cost of performing repetitive asteroid-rendezvous missions. The methods developed in the competition enable the mining of 161 asteroids via 20 mining ships, with a total collected mass of 11,513 kg.

To rapidly model the gravity field near elongated asteroids, an intelligent inversion method using Hopfield neural networks (HNNs) is proposed to estimate on-orbit simplified model parameters. First, based on a rotating mass dipole model, the gravitational field of asteroids is characterized using a few parameters. To solve all the parameters of this simplified model, a stepped parameter estimation model is constructed based on different gravity field models. Second, to overcome linearization difficulties caused by the coupling of the parameters to be estimated and the system state, a dynamic parameter linearization technique is proposed such that all terms except the parameter terms are known or available. Moreover, the Lyapunov function of the HNNs is matched to the problem of minimizing parameter estimation errors. Equilibrium values of the Lyapunov function are used as estimated values. The proposed method is applied to natural elongated asteroids 216 Kleopatra, 951 Gaspra, and 433 Eros. Simulation results indicate that this method can estimate the simplified model parameters rapidly, and that the estimated simplified model provides a good approximation of the gravity field of elongated asteroids.

High-area/mass ratio landers driven by Solar Radiation Pressure (SRP) have potential applications for future asteroid landing missions. This paper develops a new convex optimization-based method for planning trajectories driven by SRP. A Minimum Landing Error (MLE) control problem is formulated to enable planning SRP-controlled trajectories with different flight times. It is transformed into Second Order Cone Programming (SOCP) successfully by a series of different convexification technologies. A trust region constraint and a modified MLE objective function are used to guarantee the convergence performance of the optimization algorithm. Thereafter, the SRP-driven trajectory optimal control problem is converted equivalently into a sequence of convex optimal control problems that can be solved effectively. A set of numerical simulation results has verified the effectiveness and feasibility of the proposed optimization method.