Sensorless State Estimation and Control for Agile Cable-Suspended Payload Transport by Quadrotors

TL;DR

This paper introduces a novel control and sensorless estimation method for cable-suspended payload transport by UAVs, improving accuracy and performance without direct load measurements.

Contribution

It employs the Udwadia-Kalaba method for explicit dynamic modeling and integrates load state estimation into NMPC, advancing aerial payload manipulation techniques.

Findings

Explicit load dynamics inclusion reduces trajectory errors

Sensorless estimation effectively predicts load states

Experimental results outperform previous incomplete-model strategies

Abstract

This work proposes a novel control and estimation approach for aerial manipulation of a cable-suspended load using Unmanned Aerial Vehicles (UAVs). Common approaches in the state of the art have practical limitations, relying on direct load measurements and Lagrangian methods for dynamic modeling. The lack of a straightforward dynamic model of the system led us to propose adopting the Udwadia-Kalaba method to explicitly incorporate the cable's geometric constraints. This formulation allowed for the consistent derivation of the tension force and its direct integration into the NMPC prediction model. Additionally, we propose a sensorless load state estimation based on the same geometric constraints. Results from real-robot experiments demonstrated that the explicit inclusion of load dynamics in the optimization problem significantly reduces trajectory-tracking errors and yields better overall performance compared to strategies based on incomplete models.