China is exploring the potential of artificial intelligence (AI) to enhance the success of its ambitious mission to the outer boundaries of the solar system, according to a newly published research paper. The study highlights how AI could address the unique challenges of deep-space missions, including uncertain environments, complex mission dynamics, diverse scientific payloads, long detection distances, and prolonged communication delays with limited data transmission rates.
A diagram of our heliosphere. For the first time, scientists have mapped the heliopause, which is the boundary between the heliosphere (brown) and interstellar space (dark blue). Credit: NASA/IBEX/Adler Planetarium
The paper, authored by researchers from the Beijing Institute of Technology (BIT), China’s Deep Space Exploration Laboratory (DSEL), and the Shanghai Academy of Spaceflight Technology (SAST), discusses how AI can increase the autonomy of spacecraft and reduce reliance on Earth-based operations. AI is expected to assist with data processing, autonomous perception and decision-making, and efficient computing. The research was published in the Journal of Deep Space Exploration.
Chinese space officials have previously indicated their intention to send spacecraft to the head and tail of the heliosphere, the boundary where solar wind meets interstellar space, aiming to reach a distance of 100 astronomical units (AU) from Earth by 2049. A longer-term objective targets 1,000 AU by the end of the century. The proposed mission would involve two spacecraft powered by radioisotope thermoelectric generators (RTGs), utilizing flybys of Jupiter and potentially exploring other planets and Kuiper Belt objects. The scientific goals include studying interplanetary dust, the interstellar medium, and cosmic phenomena such as Anomalous Cosmic Rays and the "hydrogen wall" at the edge of the solar system. Tentative payloads may include optical cameras, dust and
particle analyzers, spectrometers, and magnetometers.
Schematic diagram of an RTG-based Chinese heliosphere spacecraft. Credit: Scientia Sinica
The China National Space Administration (CNSA) officially launched the feasibility study for the solar system boundary mission in 2020, with the project included in China’s latest space white paper in 2021. Solar system boundary exploration was also featured in a long-term space science roadmap published in October. While official updates on the mission have been scarce, the recent paper provides indirect insights into its progress and planning. China has already experimented with AI in space exploration, such as in the Chang’e-6 lunar sample return mission, where a micro rover employed AI to capture images of the lander on the Moon’s far side. AI is also expected to play a role in the upcoming Chang’e-8 lunar south pole mission. Meanwhile, NASA has integrated AI into missions like the Perseverance Mars rover.
AI could significantly enhance spacecraft autonomy for deep-space missions, particularly in data management. Given the vast distances involved, AI-driven data processing can ensure that only essential information is transmitted back to Earth. AI can also clean data to remove inconsistencies before transmission, while data fusion techniques can integrate inputs from multiple sensors to improve accuracy. Advanced AI-driven data compression techniques, such as auto-encoders, may help minimize the volume of transmitted data while preserving critical scientific insights.
Another key AI application is autonomous perception, enabling spacecraft to analyse and respond to unknown environments without direct human intervention. AI algorithms could detect and react to rare but scientifically valuable events, such as solar storms or asteroid impacts. Deep convolutional neural networks could improve multi-source data fusion, refining image processing capabilities. AI-driven health monitoring systems could continuously assess spacecraft hardware, predicting potential failures to enhance mission reliability and longevity.
AI-based autonomous decision-making capabilities could further strengthen mission resilience. AI-powered navigation and control systems could optimize spacecraft trajectories and execute course adjustments with minimal input from Earth. AI-driven mission planning, potentially leveraging reinforcement learning, may enable real-time decision-making based on environmental feedback, allowing the spacecraft to adapt to changing conditions and efficiently allocate resources. Furthermore, AI-based fault management systems could diagnose and correct malfunctions autonomously, mitigating risks posed by long communication delays.
Efficient computing is another vital aspect of deep-space missions, given the limited processing power onboard spacecraft. AI-assisted computing could focus on developing lightweight algorithms that require minimal computational resources while still delivering high performance. This approach would ensure AI’s effective deployment in deep-space environments.
Historically, only a few spacecraft have ventured toward the solar system’s boundary or beyond, including Pioneer 10 and 11, Voyager 1 and 2, the Interstellar Boundary Explorer (IBEX), and New Horizons. China’s apparent intention to incorporate AI into its own interstellar mission underscores the growing role of AI in space exploration. By leveraging cutting-edge AI technologies, China aims to enhance mission capabilities, increase spacecraft autonomy, and pave the way for more sophisticated deep-space exploration in the future.
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