Objective: This article consists of a systematic review of the literature whose objective is to describe the use of Artificial Intelligence in the prevention of collisions between satellites, as well as to characterize the techniques and performances employed to identify critical approaches and plan maneuvers. Theoretical Framework: This review is based on scientific literature on orbital monitoring and AI algorithms obtained from the Web of Science and Scopus databases, using the acronym PICOC to define the keywords that underpin current space collision prevention strategies. Method: This systematic review was conducted in a systematic and impartial manner and reported according to PRISMA guidelines. Results and Discussion: Artificial Intelligence techniques were found to be highly effective in preventing collisions, performing distinct functions, the integration of which enhances the efficiency of the results obtained. Research Implications: The implications of this research provide practical and theoretical support for improving Artificial Intelligence techniques, promoting greater space safety, orbital sustainability, optimized use of resources, and mitigation of catastrophic risks. Originality/Value: The relevance and value of this research are evidenced by providing a solid basis for proposing new solutions.
Zotovici et al. (Fri,) studied this question.