🤖 AI Summary
This study addresses the stability and coordination challenges of multi-UAV cooperative slung-load transportation under external disturbances and unmodeled dynamics by proposing a tension-aware control framework for dual UAVs. At the hardware level, a compact custom force sensor is designed to measure anchor-point interaction forces in real time. At the algorithmic level, a tension-aware cascaded control architecture is developed, wherein an outer loop compensates for cable tension to enhance system robustness. Validated through both simulations and indoor experiments, the proposed approach significantly improves system stabilization, multi-agent coordination, and disturbance rejection under positional uncertainties.
📝 Abstract
Cooperative payload transportation using multiple \textit{Unmanned Aerial Vehicles} (UAVs) poses challenges in stability, coordination, and robustness, especially under external disturbances and unmodeled dynamics. This work proposes a dual-UAV payload transportation framework supported by a compact, custom-designed force sensor measuring the interaction force at the UAV cable anchor point. The sensor design and mathematical model are presented, and its performance is characterized through static and dynamic tests evaluating linearity, hysteresis, repeatability, and crossload. The control architecture follows a cascade structure: fast inner loops handle vehicle stabilization, while outer loops are designed to compensate for the measured forces. The approach is validated through simulations and indoor experiments under position uncertainty. Payload-drop and constrained-space tests assess the proposed sensing and control architecture against literature-based distributed references, showing improved stabilization, coordination, and disturbance rejection. A video of the experiments is available at: https://youtu.be/rIw9-fvV8Qw.