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ICRA 2026 | How can coupled disturbances be estimated with high precision and low computational cost?

Achieving high-precision control for robotic systems is hindered by the low-fidelity dynamical model and external disturbances. Especially, the intricate coupling between internal uncertainties and external disturbances further exacerbates this challenge.

To address this challenge, Beihang University will present their work at ICRA 2026, proposing a coupled disturbance estimation framework that integrates control theory with data-driven learning.

Through Chebyshev polynomial decomposition and polynomial observer design, the algorithm achieves high-precision estimation of complex coupled disturbances with low computational cost, without presetting disturbance bounds.

In indoor wind-disturbance experiments, NOKOV motion capture system provided real-time pose feedback for the UAV control loop, helping validate the effectiveness of the proposed method.

Learn more: https://en.nokov.com/motion-capture-applications/robotics-engineering/drones-swarms.html