Problem
Research questions and friction points this paper is trying to address.
planetary drones
localization
tethered UAVs
inertial navigation
payload constraints
Tether-Inertial Localization for Planetary Drones
🤖 AI Summary
Planetary drones are constrained by limited payload capacity, making it difficult to integrate high-power localization systems and thereby restricting both flight duration and positioning accuracy. This work proposes a lightweight, vision-free, and GNSS-independent relative localization approach that leverages a tether for power and computational support. It uniquely integrates tether length, angular measurements, and inertial data, combining an analytical catenary model with Gaussian process regression for error compensation. Evaluated over 37 minutes of multi-trajectory flight, the method achieves an average RMSE of 7.4 cm, which improves to 5.2 cm after optimization—representing an order-of-magnitude enhancement in accuracy over existing techniques.
📝 Abstract
Recent developments in planetary exploration have shown the potential of Unmanned Aerial Vehicles (UAVs), such as the Ingenuity helicopter that provided valuable mapping data. However, limited payload capabilities constrain the flight times and compute available for localization, which restrict their applicability. By providing a tethered connection, issues such as battery and computational constraints are offloaded to the base rover. At the same time, the cable can be exploited for non-drifting localization. This work presents a novel Tether-Inertial Localization approach that uses tether length and angle measurements to estimate the UAV position relative to its base. The method combines a computationally efficient analytical catenary model with a Gaussian Process (GP) residual error compensation. This accounts for systematic sensor inaccuracies and model limitations. Experimental validation across circular, triangular, and figure-eight trajectories with tether lengths up to 4.5 m and a total flight time of 37 minutes demonstrates the effectiveness of the proposed approach. Using only tether-based position estimates for feedback, the analytical catenary model achieves an average RMSE of 7.4 cm, which is further reduced to 5.2 cm through GP-based residual compensation, one order of magnitude better than the state-of-the-art. These results establish Tether-Inertial Localization as a practical alternative to vision- and GNSS-based localization for Tethered Unmanned Aerial Vehicles (TUAVs).
Innovation
Methods, ideas, or system contributions that make the work stand out.
Tether-Inertial Localization
Catenary Model
Gaussian Process
Tethered UAV
Non-drifting Localization
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