Towards Fully Onboard State Estimation and Trajectory Tracking for UAVs with Suspended Payloads

TL;DR

This paper presents a practical onboard state estimation and control framework for UAVs with suspended payloads, using only standard sensors, and demonstrates its effectiveness through simulations and outdoor experiments.

Contribution

It introduces a fully onboard, sensor-efficient approach for payload tracking and control, avoiding reliance on external tracking systems or specialized payload instrumentation.

Findings

Performance comparable to ground-truth based control (<6% degradation)

Robustness to payload parameter variations

Successful outdoor validation with off-the-shelf hardware

Abstract

This paper addresses the problem of tracking the position of a cable-suspended payload carried by an unmanned aerial vehicle, with a focus on real-world deployment and minimal hardware requirements. In contrast to many existing approaches that rely on motion-capture systems, additional onboard cameras, or instrumented payloads, we propose a framework that uses only standard onboard sensors--specifically, real-time kinematic global navigation satellite system measurements and data from the onboard inertial measurement unit--to estimate and control the payload's position. The system models the full coupled dynamics of the aerial vehicle and payload, and integrates a linear Kalman filter for state estimation, a model predictive contouring control planner, and an incremental model predictive controller. The control architecture is designed to remain effective despite sensing limitations and estimation uncertainty. Extensive simulations demonstrate that the proposed system achieves performance comparable to control based on ground-truth measurements, with only minor degradation (< 6%). The system also shows strong robustness to variations in payload parameters. Field experiments further validate the framework, confirming its practical applicability and reliable performance in outdoor environments using only off-the-shelf aerial vehicle hardware.