Autonomous drone GNC for planetary exploration

Planetary exploration poses unique challenges due to unknown terrain, communication delays, and the necessity for autonomous operation in harsh environments. This thesis focuses on the development and implementation of an autonomous Guidance, Navigation, and Control (GNC) system for a drone intended to support planetary surface missions. The primary objective is to achieve real-time, reliable, and efficient navigation and control in Global Navigation Satellite Systems (GNSS)-denied environments, such as Mars. The proposed system integrates onboard sensor fusion for localization—leveraging monocular odometry—with path planning algorithms to enable efficient trajectory generation. A central design consideration is feasibility: the selection of sensors and components is based on current or near-future space-qualified technologies, with realistic performance characteristics accounted for throughout development. System performance was validated in a simulated environment that incorporated representative planetary terrain and constraints. This work contributes to the advancement of autonomous aerial robotics for future space missions, enhancing the capabilities of planetary surface exploration and scientific data collection.