Communication latency presents a significant challenge for remotely operated planetary rovers by reducing operator situational awareness and increasing the risk of navigation errors, collisions, and operational inefficiencies. This study addresses the effects of communication delays on remote rover operations through the design, development, and validation of an AI-driven digital twin framework for a NASA-inspired RASSOR rover platform. The resulting cyber-physical system integrates a modular rover platform, LiDAR, ultrasonic sensors, camera systems, teleoperation capabilities, and a virtual rover model developed in NVIDIA Isaac Sim. A hybrid Lean Six Sigma DMAIC/DMADV methodology was used to identify the limitations of traditional “move-and-wait” teleoperation and guide the development of a predictive operational framework designed to improve rover awareness under simulated three-second communication delays. Experimental testing demonstrated improved obstacle detection, enhanced navigation reliability, reduced collision risk, successful synchronization between the physical rover and its digital twin, and the establishment of a robust data-collection platform for future autonomy development. The main focus was on the design, integration, testing, and validation of the rover and digital twin architecture. This study delivered a functional cyber-physical system that advances rover operations from a reactive control paradigm toward predictive and semi-autonomous decision support. The resulting framework establishes a foundation for future research and development in autonomous lunar surface operations, digital engineering, and resilient robotic systems for space exploration.

Keywords

Digital twin, planetary robotics, communication latency, Lean Six Sigma and NVIDIA Isaac Sim.