Search Results for author: Yongqian Xiao

Found 3 papers, 0 papers with code

DDK: A Deep Koopman Approach for Dynamics Modeling and Trajectory Tracking of Autonomous Vehicles

no code implementations27 Oct 2021 Yongqian Xiao

In this paper, the approach based on the Koopman operator named deep direct Koopman (DDK) is proposed to identify the model of the autonomous vehicle and the identified model is a linear time-invariant (LTI) version, which is convenient for motion planning and controller design.

Autonomous Driving Motion Planning +1

CKNet: A Convolutional Neural Network Based on Koopman Operator for Modeling Latent Dynamics from Pixels

no code implementations19 Feb 2021 Yongqian Xiao, Xin Xu, QianLi Lin

In this paper, a novel Koopman-based deep convolutional network, called CKNet, is proposed to identify latent dynamics from raw pixels.

Deep Neural Networks with Koopman Operators for Modeling and Control of Autonomous Vehicles

no code implementations5 Jul 2020 Yongqian Xiao, Xinglong Zhang, Xin Xu, Xueqing Liu, Jiahang Liu

Furthermore, a data-driven model predictive controller with the learned Koopman model is designed for path tracking control of autonomous vehicles.

Autonomous Driving

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