Intelligent Tracking and Trajectory Navigation Approach for Blimp Robot

Recently, there has been increasing interest in autonomous navigation for the Unmanned Airship Vehicles (UAV) in indoor environments since they have the ability to navigate in low altitude and low speed for exploration applications. In this paper, we presented a two layer fuzzy approach to light-weight embedded blimp system navigates in unknown environment. The fuzzy rules base for the first layer is trained using possibilities distributions and fuzzy sets based on experimental data. This approach is able to control the main behaviors of the blimp: avoid obstacles, maintain at certain altitude, track ground robot and rotate blimp around OZ axis. It has the ability to quickly provide a possibly trajectory for the blimp in case a wall or object is detected in the path. The experiments results show that the trajectory navigation system is efficient and reliable in unknown environments.