TetherBot: A Power-Tethered sUAS Platform for Autonomous Vertical Atmospheric Profiling
Daniel Rico, Francisco Munoz-Arriola, Justin Bradley
AI summary
Problem
Current atmospheric monitoring methods lack the spatial resolution, endurance, and measurement fidelity required to capture fine-scale vertical gradients of greenhouse gases and meteorological variables in agroecosystems.
Approach
TetherBot is a lightweight, friction-driven robot that autonomously traverses a flexible power tether hoisted by a drone, collecting synchronized environmental data while avoiding propeller wash and thermal biases.
Key results
- Reliable autonomous vertical traversal across a 40 m transect
- Consistent altitude tracking via barometric pressure and detection of subtle temperature stratification
- High-resolution relative humidity mapping revealing surface-layer variability
- CO2 measurements limited by compact sensor noise, highlighting the need for higher-fidelity analyzers
Why it matters
This architecture provides a scalable, persistent alternative to fixed towers and short-lived drones for high-precision carbon monitoring and agroecosystem flux studies.
Abstract
Resolving vertical gradients of atmospheric vari- ables in agroecosystems is essential for understanding surface- atmosphere exchange. It is also critical for emerging carbon monitoring frameworks. Existing methods, such as eddy covari- ance towers and satellite remote sensing, provide observations with limited spatial resolution, leaving fine-scale structure un- dersampled. This work introduces TetherBot, a tethered robotic profiler integrated into the Tethered Aircraft Uncrewed System. The robot traverses a hoisted power tether, enabling persistent vertical profiling with synchronized sensing and telemetry. Field experiments across a 40 m transect demonstrated reliable operation. Barometric pressure provided consistent altitude, temperature resolved subtle stratification, and relative humidity revealed surface-layer variability. Carbon dioxide measure- ments were dominated by sensor noise, highlighting the need for higher-fidelity analyzers. These results demonstrate the feasibility of tethered robotic profiling as a viable approach for atmospheric monitoring. They establish a foundation for future multi-robot arrays and high-precision flux applications.