Yongqian Xiao

According to our database, Yongqian Xiao authored at least 8 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

AMARL: An Attention-Based Multiagent Reinforcement Learning Approach to the Min-Max Multiple Traveling Salesmen Problem.

Hao Gao, Xing Zhou, Xin Xu, Yixing Lan, Yongqian Xiao

IEEE Trans. Neural Networks Learn. Syst., July, 2024

A deep Koopman operator-based modelling approach for long-term prediction of dynamics with pixel-level measurements.

Yongqian Xiao, Zixin Tang, Xin Xu, Xinglong Zhang, Yifei Shi

CAAI Trans. Intell. Technol., February, 2024

Vector Field-Guided Learning Predictive Control for Motion Planning of Mobile Robots with Unknown Dynamics.

Yang Lu, Weijia Yao, Yongqian Xiao, Xin Xu

CoRR, 2024

2023

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

Yongqian Xiao, Xinglong Zhang, Xin Xu, Xueqing Liu, Jiahang Liu

IEEE Trans. Intell. Veh., January, 2023

DDK: A Deep Koopman Approach for Longitudinal and Lateral Control of Autonomous Ground Vehicles.

Yongqian Xiao, Xinglong Zhang, Xin Xu, Yang Lu, Junxiang Li

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2021

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

Yongqian Xiao

CoRR, 2021

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

Yongqian Xiao, Xin Xu, Qianli Lin

CoRR, 2021

2020

A deep learning framework based on Koopman operator for data-driven modeling of vehicle dynamics.

Yongqian Xiao, Xinglong Zhang, Xin Xu, Xueqing Liu, Jiahang Liu

CoRR, 2020