This paper presents a novel approach to indoor navigation of an aerostatic drone using Visual Simultaneous Localization and Mapping (v-SLAM) techniques. By adapting the RTAB-Map SLAM algorithm, we have developed a system capable of accurately mapping and localizing the drone within indoor environments. The drone, designed for airship-based operations, is equipped with advanced sensors and utilizes the Dynamic Window Approach (DWA) local planner for efficient path planning. Our methodology aims to enhance the drone’s ability to navigate complex indoor spaces autonomously, leveraging the unique characteristics of aerostatic flight to overcome challenges posed by traditional UAVs. Through extensive simulations and real-world testing, we demonstrate the effectiveness of our approach in achieving high levels of autonomy and precision in indoor navigation tasks. This work contributes to the advancement of drone technology for indoor applications, offering a promising solution for various sectors requiring autonomous navigation capabilities within confined spaces.