Design and Control of a Miniature Indoor Blimp: A Safer, Quieter, and Resilient Alternative for Indoor Exploration and Surveillance

This thesis focuses on the development and implementation of a miniature indoor blimp as an alternative unmanned aerial vehicle (UAV) for indoor exploration and surveillance applications. Unlike traditional quadcopters, the blimp offers a safer, quieter, and more resilient solution for indoor environments. The blimp's key feature is its exceptional spatial position control, achieved through control theory principles and state-of-the-art research. This control capability enables precise movement and hovering, making it suitable for tasks requiring accuracy and stability. Additionally, the blimp incorporates autonomous navigation, allowing it to follow specific trajectories with high accuracy, benefiting applications such as repetitive surveillance or exploration of unknown environments. The blimp's extended flight time is attributed to its use of helium, providing lift and energy efficiency. Furthermore, the blimp integrates a neural network-based obstacle avoidance system, enhancing its safety, reliability, and adaptability to the environment through machine learning. Throughout the thesis, the design intricacies, control mechanisms, and comparative analysis with quadcopters are explored. This comprehensive study contributes to the understanding of miniature blimps as indoor exploration vehicles, emphasizing their advantages and inspiring further research and innovation in the field of indoor aerial vehicles.