This research concentrates on the design and development of a single-rotor aerial robot inspired by the maple seed. The objective is to provide an efficient system for precise missions with autonomous capabilities. The robot, equipped with advanced sensors, intelligent cameras, and artificial intelligence algorithms, is capable of stable cylindrical flight, navigation in confined spaces, and accurate data collection. The system's dynamic equations were extracted, and an optimal control strategy was formulated using the pseudospectral method. To ensure robustness against environmental disturbances such as crosswinds, a robust optimal guidance system based on a neuro-fuzzy model was designed. Additionally, a model predictive controller (MPC) was developed to predict future states and optimize inputs in real-time. This combination ensured the system's accuracy and stability under challenging conditions. Simulation results demonstrated that this robot, with its optimal energy consumption and high resilience, is a suitable option for sensitive operations such as search and rescue. This research represents a significant step forward in the development of intelligent and sustainable aerial systems.