Intelligent Exploration

Abstract

This paper investigates the application of systems engineering to integrate optical communications with Artificial Intelligence (AI) for autonomous exploration of extraterrestrial environments. Focusing on deep-space missions, it examines AI-enabled robotic systems supported by high-bandwidth, low-latency optical communication to assess planetary habitability. Using systems engineering methodologies, the research addresses key challenges, including integration feasibility, scalability, and robustness under interplanetary constraints.

This research hypothesizes that a systems engineering framework can effectively integrate AI software, optical communication infrastructure, and robotic platforms into a cohesive and scalable solution for space exploration. It addresses three key questions: (1) What systems engineering methodologies are needed to design and manage this integration? (2) What factors influence the feasibility of implementing such systems, considering technological, operational, and environmental challenges? (3) Can systems engineering approaches ensure robustness and scalability under interplanetary constraints? By applying these principles, this study seeks to identify critical design considerations for creating efficient and resilient solutions for future space missions.