HELSINKI — Researchers are examining how artificial intelligence technologies could support a planned Chinese mission to the boundaries of the solar system, according to a new paper.
Artificial intelligence can help with the unique challenges of missions to the edge of the solar system, according to the paper, which include an unknown environment, complex mission dynamics, diverse scientific payloads, uncertain exploration targets, long detection distances and long communication delays with limited data rates.
AI can enhance autonomy and reduce dependence on Earth through assisting data processing, autonomous perception and decision-making and efficient computing, according to authors from institutions including the Beijing Institute of Technology (BIT), China’s Deep Space Exploration Laboratory (DSEL), and the Shanghai Academy of Spaceflight Technology (SAST). The paper was published in the Journal of Deep Space Exploration.
Chinese space officials have previously stated that a mission to the head and tail of the heliosphere is being considered, with the aim of reaching a distance of 100 astronomical units (with 1 AU equivalent to the average Sun-Earth distance) by 2049. A longer-term goal is to reach a distance of 1,000 AU by the end of the century.
The mission, according to previous reports, would see the pair of radioisotope thermoelectric generator-powered spacecraft journey towards the head and tail of the heliosphere, using flybys of Jupiter and potentially visiting other planets and Kuiper belt objects in the outer solar system. Science goals include studying interplanetary dust, the interstellar medium, and phenomena such as Anomalous Cosmic Rays and the “hydrogen wall” at the boundary of the solar system and interstellar space. Tentative payloads include a range of optical cameras, dust and particle analyzers, a spectrometer and magnetometer.
The China National Space Administration officially organized and launched the demonstration of the implementation plan for a solar system boundary exploration project in 2020, and plans to study the mission were included in China’s most recent space white paper in 2021. Solar system boundary exploration was noted in a long-term space science roadmap published in October.
There have, however, been few official updates on the mission. The paper, published in late 2024, provides a somewhat indirect update along with a glimpse into planning for the mission. China has used AI in space in a limited manner previously, for example in the recent Chang’e-6 mission sample return mission. A micro rover used AI to take an image of the lander on the far side of the moon. It is also expected to be used for rovers on the future Chang’e-8 lunar south pole mission. NASA has also used AI in space exploration, for example embedded in the Perseverance Mars rover.
AI for solar system boundary exploration
Artificial Intelligence could play a crucial role in China’s plans for solar system boundary exploration, according to the papers, enhancing spacecraft autonomy and reducing reliance on Earth-based control.
AI-driven data processing can help ensure that spacecraft transmit only essential information, given long distances and constrained data rates. AI-driven data cleaning can also remove errors and inconsistencies before transmission, while data fusion combines inputs from multiple sensors to increase accuracy. Additionally, AI-based data compression techniques such as using autoencoders, which reduce data volume by identifying and encoding only the most critical information, may significantly reduce the volume of information sent back to Earth without losing critical details, a vital capability given the vast distances involved in such missions.
AI may also enable autonomous perception, allowing spacecraft to sense and model unknown environments effectively. By employing advanced AI algorithms, spacecraft can autonomously detect and react to rare but scientifically valuable events, such as solar storms or asteroid impacts. The authors suggest deep convolutional neural networks can effectively improve the performance of multi-source detection data fusion processing for image processing. Additionally, AI-driven probe health monitoring systems can assess hardware status continuously, predicting potential failures to ensure mission longevity and reliability.
Another possible benefit is autonomous decision-making capabilities powered by AI which could further strengthen mission resilience. AI-driven navigation and control systems can optimize trajectories and make course adjustments with minimal Earth-based intervention. Mission planning systems leveraging AI—such as Reinforcement Learning (RL) to enable autonomous decision-making and real-time mission planning based on feedback from the environment—may also be able to adapt to changing conditions, prioritize tasks autonomously, and ensure efficient use of limited resources. Additionally, AI-based fault management systems will diagnose and self-correct spacecraft malfunctions in real-time, enhancing mission safety, without a back-and-forth between Earth and distant spacecraft with significant light-time delays.
Efficient computing meanwhile can ameliorate the challenges of limited processing power onboard spacecraft. An AI-assisted approach could emphasize developing lightweight AI algorithms that require minimal computational resources, ensuring their effective deployment in deep space, the authors note.
Only a handful of spacecraft have been launched towards the edges of the solar system or heliopause. These include Pioneer 10 and 11, Voyager 1 and 2, the Interstellar Boundary Explorer (IBEX), and the New Horizons mission. China’s apparent intention to utilize artificial intelligence for its own solar system boundary mission underscores the growing significance of AI in space exploration, highlighting how such cutting-edge technologies could enhance mission capabilities in deep space.
