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20232026
most citedData-Driven Optimal Control of Tethered Space Robot Deployment with Learning Based Koopman Operator

11 citations · 11 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2026

Data-Driven Modeling and Control for Tethered Space Systems with Koopman-Informed Graphs

Ao Jin, Yifeng Ma, Panfeng Huang +1

Modeling tethered space systems is critical for advanced orbital operations. Flexible components such as tethers and space nets are integral to these systems but present significan…

cs.RO2026

A Self-Rotating Tri-Rotor UAV for Field of View Expansion and Autonomous Flight

Xiaobin Zhou, Zihao Zheng, Aoxu Jin +2

Unmanned Aerial Vehicles (UAVs) perception relies on onboard sensors like cameras and LiDAR, which are limited by the narrow field of view (FoV). We present Self-Perception INertia…

eess.SY2025

Differentiable Physics-Informed Adaptive Koopman Control for Stable Flight under Unknown Disturbances

Ao Jin, Qiujin Liang, Tao Zhang +2

Uncertainties and disturbances in robotic systems, such as aerodynamic forces, are fundamentally outcomes of physical interactions with the environment, manifesting as learnable sp…

eess.SY2025

Enhanced Robust Tracking Control: An Online Learning Approach

Ao Jin, Weijian Zhao, Yifeng Ma +2

This work focuses the tracking control problem for nonlinear systems subjected to unknown external disturbances. Inspired by contraction theory, a neural network-dirven CCM synthes…

cs.RO2024

Neural Predictor for Flight Control with Payload

Ao Jin, Chenhao Li, Qinyi Wang +3

Aerial robotics for transporting suspended payloads as the form of freely-floating manipulator are growing great interest in recent years. However, the force/torque caused by paylo…

eess.SY2023★ 11 cited

Data-Driven Optimal Control of Tethered Space Robot Deployment with Learning Based Koopman Operator

Ao Jin, Fan Zhang, Panfeng Huang

To avoid complex constraints of the traditional nonlinear method for tethered space robot (TSR) deployment, this paper proposes a data-driven optimal control framework with an impr…