This research presents the development and validation of an advanced Unmanned Aircraft System (UAS) application capable of autonomously guiding a slung load, specifically an antenna designed for groundwater scanning, along a predefined trajectory with high precision and stability.

This work aims to enhance UAS operational capabilities in environmental monitoring tasks, ensuring accurate data collection and efficient deployment in challenging terrains. A key aspect of this research is creating a comprehensive simulation environment to model the dynamics of the slung load system. This environment enables the testing and refinement of control, guidance, and navigation algorithms before real-world implementation, significantly contributing to the field by improving UAS performance in slung load operations.

The core contributions include the development of effective control methods for stabilizing slung loads tethered to UAS, ensuring smooth flight while maintaining the correct attitude and altitude. Additionally, a guidance system was created to enable the UAS to fly predefined trajectories with enhanced stability of the slung load. These advancements address crucial challenges in UAS applications, particularly ensuring stable and accurate slung load transport.

The project’s hypothesis — Is it possible to develop a UAS-based slung load system that can successfully carry an antenna suspended by tethers along a predefined trajectory for an extended period across various environments? —was validated through extensive simulations and field experiments. The research findings contribute to broader UAS applications, particularly where high-precision data collection and stability are essential. The results provide practical insights for future developments in UAS technology, particularly for environmental monitoring and other applications requiring UAS to transport and stabilize dynamic loads. Further research areas are suggested, such as improving tether control methods, integrating hybrid UAS systems for extended flight durations, and refining the navigation and guidance algorithms for more complex environments.