Weibin Gu

Koopman Identification of Nonlinear Systems via Reservoir Liftings

Weibin Gu, Chen Yang, Lu Shi

Learning tractable linear representations of nonlinear dynamical systems via Koopman operator theory is often hindered by dictionary selection, temporal memory encoding, and numerical ill-conditioning. Inspired by Reservoir Computing (RC) paradigm, this paper introduces the RC-Koopman framework, which interprets reservoir as a stateful, …

Koopman Identification of Nonlinear Systems via Reservoir Liftings

Weibin Gu, Chen Yang, Lu Shi

Learning tractable linear representations of nonlinear dynamical systems via Koopman operator theory is often hindered by dictionary selection, temporal memory encoding, and numerical ill-conditioning. Inspired by Reservoir Computing (RC) paradigm, this paper introduces the RC-Koopman framework, which interprets reservoir as a stateful, …

A 26-Gram Butterfly-Inspired Robot Achieving Autonomous Tailless Flight

Weibin Gu, Chenrui Feng, Lian Liu, Chen Yang et autres

cn, it, uz (code pays fourni par la source)

Koopman Identification of Nonlinear Systems via Reservoir Liftings

Weibin Gu, Chen Yang, Lu Shi

Learning tractable linear representations of nonlinear dynamical systems via Koopman operator theory is often hindered by dictionary selection, temporal memory encoding, and numerical ill-conditioning. Inspired by Reservoir Computing (RC) paradigm, this paper introduces the RC–Koopman framework, which interprets reservoir as a stateful, …

cn (code pays fourni par la source)

DISCOVERSE: Efficient Robot Simulation in Complex High-Fidelity Environments

Yufei Jia, Guangyu Wang, Yuhang Dong, Jinfu Wu et autres

We present Discoverse, the first unified, modular, open-source 3DGS-based simulation framework for Real2Sim2Real robot learning. It features a holistic Real2Sim pipeline that synthesizes hyper-realistic geometry and appearance of complex real-world scenarios, paving the way for analyzing and bridging the Sim2Real gap. Powered …

cn, us (code pays fourni par la source)

Learning uncertainties online for quadrotor flight control: A comparative study

Weibin Gu, Jiance Zhao, Alessandro Rizzo

Abstract Traditional adaptive and robust control methods sometimes struggle to address the complex and dynamic uncertainties inherent in quadrotor flight, frequently resulting in overly conservative or unstable behavior due to reliance on presumed uncertainty bounds. To overcome these limitations, we propose a …

cn, it (code pays fourni par la source)

Localization Handover for Mobile Robots: A Seamless Indoor-Outdoor Approach

Andrea Usai, Weibin Gu, Alessandro Rizzo

Abstract This paper presents a seamless indoor-outdoor localization approach for autonomous mobile robots by integrating multiple technologies: Ultra-Wideband (UWB) for high-precision indoor positioning, Global Positioning System (GPS) for outdoor global navigation, odometry for detailed granularity, and an Inertial Measurement Unit (IMU) for …

it, cn (code pays fourni par la source)

Robust adaptive control for aggressive quadrotor maneuvers via SO ( 3 ) and backstepping techniques

Weibin Gu, Stefano Primatesta, Alessandro Rizzo

For decades, a number of nonlinear control methodologies such as backstepping control and model predictive control have been studied to guarantee the stability and performance of systems under control. Most of these designs were based on local coordinates like Euler angles or …

it, cn (code pays fourni par la source)

Online Residual Learning Using Interpretable Reservoir Computing for Quadrotor Control

Weibin Gu, Alessandro Rizzo

Quadrotors, valued for their mobility and cost-effectiveness, have found widespread use in applications such as aerial photography and infrastructure inspection. However, their complex and nonlinear dynamics make them sensitive to uncertainties. In dynamic scenarios with online data but little-to-no prior knowledge of …

it (code pays fourni par la source)

Physics-informed Neural Network for Quadrotor Dynamical Modeling

Weibin Gu, Stefano Primatesta, Alessandro Rizzo

The explosive growth of civil applications of Unmanned Aerial Vehicles (UAVs) calls for control algorithms that enable safe and trustworthy operations, especially in complex environments to facilitate real-world deployment. Although Model-Based Control (MBC) has found great applicability in the last decades, it …

it (code pays fourni par la source)

UAV Model-based Flight Control with Artificial Neural Networks: A Survey

Weibin Gu, Kimon P. Valavanis, Matthew J. Rutherford, Alessandro Rizzo

us, it (code pays fourni par la source)

Autonomous Wind Turbine Inspection using a Quadrotor

Weibin Gu, Dewen Hu, Liang Cheng, Yabing Cao et autres

There has been explosive growth of wind farm installations in recent years due to the fact that wind energy is gaining worldwide popularity. However, the maintenance of these offshore or onshore wind turbines, especially in remote areas, remains a challenging task. In …

us, it (code pays fourni par la source)