Embedding Arti-Mach in Aerospace Engineering

Space exploration and deep-space missions have increasingly been in demand lately – For instance, advanced levels of spacecraft autonomy, precision, and adaptability. However, there were limitations in onboard computational resources and significant delays in communication with Earth which posed critical challenges in the real-time navigation and decision-making amidst crucial operations. This research paper brings forth an innovative hybrid framework uniting Cloud-based AI and Digital Twin technology to enhance real-time navigation and operability for spacecraft. A Digital Twin is basically a dynamic, real-time virtual replica of the spacecraft hosted on terrestrial cloud infrastructure which is maintained through prioritized telemetry data transmitted from the spacecraft to the digital twin such that the digital twin stays in sync with the spacecraft as precisely as possible. Advanced AI models deployed on the cloud continuously monitor, simulate, analyse, and forecast spacecraft conditions, system health, navigational trajectories, and external threats that may exist in space. To be precise, we would be utilizing predictive modelling to bridge the latency gap that persists in deep-space communications, offering a strategic decision-making mechanism to the spacecraft rather than constant direct control. Though, the spacecraft would be supported by a lightweight onboard AI module which interprets the predicted instructions autonomously according to operational urgency. This research ventures through the architecture, advantages, and operational mechanisms of such a hybrid system, aiming to improve spacecraft survival chances, reduce risks, and extend the range of human exploration further into the solar system.