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Chengyu Yang

5 accepted papers

2026

Failure Detection and Recovery for Quadrotors in the Presence of Severe Rotor Failures With Multiple Model $\mathcal {L}_{1}$ Adaptive Controller

RA-L 2026

Over the last few decades, quadrotors proved to be a viable platform for improving efficiency and achieving cost savings in a variety of industries, and yet the safety of flight remains a major challenge to be guaranteed, especially in the presence of rotor failures. In this paper, we revisit the <i

Cited by 0SourceScholar
2026

MUSE: Multimodal Uncertainty Quantification of State Estimation

ICRA 2026poster

Accurate visual state estimation has been a central topic in robotics with a wide range of applications in robot navigation, autonomous driving, and autonomous flight. Recent advances in robot perception have led to significant improvements in the accuracy and robustness of state estimation, yet a f…

2026

Real-Time Linear MPC for Quadrotors on SE(3): An Analytical Koopman-Based Realization

ICRA 2026poster

This letter presents an analytical linear parameter- varying (LPV) representation of quadrotor dynamics utilizing Koopman theory, facilitating computationally efficient linear model predictive control (LMPC) for real-time trajectory track- ing. By leveraging carefully designed Koopman observables, t…

2025

Dis²Booth: Learning Image Distribution with Disentangled Features for Text-to-Image Diffusion Models

AAAI 2025technical

Personalized image generation enables customized content creation based on the text-to-image diffusion models.However, existing personalization methods focus on fine-tuning generative models to learn to generate specific single individuals or concepts, such as an image of a specific Corgi, but are u…

Cited by 0SourcePDFScholar
2025

Real-Time Linear MPC for Quadrotors on SE(3): An Analytical Koopman-Based Realization

RA-L 2025

This letter presents an analytical linear parameter-varying (LPV) representation of quadrotor dynamics utilizing Koopman theory, facilitating computationally efficient linear model predictive control (LMPC) for real-time trajectory tracking. By leveraging carefully designed Koopman observables, the

Cited by 6SourceScholar