# Using Artificial Intelligence for Space Challenges: A Survey
## 1 Introduction  
Over the past 60 years, artificial intelligence (AI) has been used in several applications, such as automated reasoning, intelligent systems, knowledge representation, and game theory, to cite some famous examples. However, recent advances in computational power, the number of available data, and new algorithms have highlighted that AI can have a crucial role in the digital transformation of society and must be a priority for any country. For this reason, the research community has devoted much effort to designing and developing new AI techniques in many strategic fields such as cybersecurity, e-Health, military applications, and smart cities. The importance of AI is witnessed by the numerous survey papers describing recent advances in AI in almost all fields. However, we have found that in recent years, AI has been strongly exploited in an important field that is not covered by any specific survey: space applications. This field includes technologies for space vehicles (spacecraft, satellites, etc.) and their communications and services for terrestrial use (weather forecasting, remote sensing, etc.). In all these cases, using AI-based solutions has given and can give many advantages. To the best of our knowledge, no survey published in the last ten years has focused on this topic. Indeed, Reference [1] focuses only on a specific branch of AI (i.e., robotics) and provides a survey on robotics and autonomous systems for space exploration. Reference [2] is limited to an interesting but very specific field of space applications, which concerns satellite communication. The only survey remotely related to this topic is Reference [3], which focuses on the following specific topics: autonomous planning and scheduling of operations, self-awareness, anomaly detection, on-board data analysis, and on-board operations and processing of Earth-observation data. However, these topics represent a specific and limited aspect of space applications (this paper received 12 citations after more than two years since its publication). In this paper, we provide a survey of the current challenges in space applications and discuss the most relevant state-of-the-art proposals. In order to present a self-containeddiscussion on the topic, we start by briefly introducing the major branches of AI exploited in this field. Then, we identify thirteen challenges related to space applications, grouped into three main categories: mission design and planning, space exploration, and Earth observation. Each challenge is defined and discussed, and the most effective AI-based solutions proposed in the literature are presented. To collect all relevant papers on this topic, Google Scholar archive was used, and we searched for the terms \"space applications\" and \"artificial intelligence\". We extended this search, also substituting the term artificial intelligence with its main branches (such as machine learning and neural networks). These searches resulted in more than 200 papers, which were filtered by excluding unpublished papers (e.g., theses) or published by low-relevance publishers. Then, we excluded papers considered out of scope for this survey after a manual check. This resulted in more than one hundred papers published in the last five years (2017-2022): these papers are presented and discussed as solutions for space application challenges. The organization of this paper allows the reader to both find the most recent solutions proposed for a given problem and to identify the problems in which a given AI-based technique has been exploited. The structure of the paper is as follows. In Section 2, we briefly provide the background on AI needed to classify the different techniques. Then, in Section 3, we present the current challenges in space applications that AI is helping to address. In Section 4, we discuss the most recent solutions proposed for addressing each challenge. In Section 5, we provide a high-level discussion about the problems and the solutions from recent years in the field of space applications.