Abstract The rapid development of AI has resulted in an unprecedented paradigm shift across various industries, with aerospace among the laureates of this transformation. This review paper attempts to explore and provide comprehensive overview of the aerospace research imperatives from the AI perspective, detailing the technical sides of the full lifecycle from vehicle design and operational optimisation to advanced air traffic management systems. By examining real-world engineering implementations, the review demonstrates how AI-driven solutions are directly addressing longstanding challenges in aerospace, such as optimising flight performance, reducing operational costs and improving system reliability. A significant emphasis is placed on the crucial roles of AI in health monitoring and predictive maintenance, areas that are pivotal for ensuring the safety and longevity of aerospace endeavors, and which are now increasingly adopted in industry for remaining useful life (RUL) forecasting and condition-based maintenance strategies. The paper also discusses AI embedded in quality control and inspection processes, where it boosts accuracy, efficiency and fault detection capability. The review provides insight into the state-of-the-art applications of AI in planetary exploration, particularly within the realms of autonomous scientific instrumentation and robotic prospecting, as well as surface operations on extraterrestrial bodies. An important case study is India’s Chandrayaan-3 mission, demonstrating the application of AI in both autonomous navigation and scientific exploration within the challenging environments of space. By furnishing an overview of the field, the paper frames the ever-important, increasing domains of AI as the forefront in the advancement of aerospace engineering and opens avenues for further discussion regarding the limitless possibilities at the juncture of intelligent systems and aerospace innovation.
Shenwai et al. (Mon,) studied this question.
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