Xiaobing Lu - IEEE Xplore Author Profile

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Author details

Xiaobing Lu

Also published under: Xiao-bing Lu

Publications

8

Citations

172

Publications by Year

20162024

Co-Authors:

Wenping ChuFuchuan DuanShibin GaoZhiwei HanJiang Jing

Show All Co-Authors (15)

Xiaobing Lu

Also published under: Xiao-bing Lu

Affiliation

China Railway Eryuan Engineering Group Company Ltd., Chengdu, China

Publication Topics

Contact Force,
Contact Line,
Contact Wire,
Finite Element,
Nonlinear Element,
Numerical Simulations,
Overhead Contact Line,
Quality Of Contact,
Stiffness Matrix,
Young’s Modulus,
Absolute Difference,
Aerodynamic Coefficients

Biography

Xiaobing Lu received the B.S. degree in automation from Lanzhou Jiaotong University, Lanzhou, China, in 2010, and the M.S. degree in electrical engineering from Southwest Jiaotong University, Chengdu, China, in 2012, where he is currently pursuing the Ph.D. degree with the School of Electrical Engineering.,His current research interests include the pantograph–catenary system modeling and pantograph active control.(Based on document published on 27 January 2016).

Publications

8

Citations

172

Publications by Year

20162024

Co-Authors:

Wenping Chu
Fuchuan Duan
Shibin Gao
Zhiwei Han
Jiang Jing

Show All Co-Authors (15)

Author's Published Works

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Showing 1-4 of 4 results

Conferences (3)

Journals (1)

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George Council(4)
Aaron M. Johnson(3)
Nathan J. Kong(3)
Shai Revzen(1)
James Zhu(1)
Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA(2)
Dept. Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, United States(1)
XPeng Robotics, Mountain View, CA, USA(1)
Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania(1)
2021 60th IEEE Conference on Decision and Control (CDC)(1)
2022 International Conference on Robotics and Automation (ICRA)(1)
IEEE Transactions on Robotics(1)
Proceedings of the 2014 International Conference on Advanced Mechatronic Systems(1)
IEEE(4)
Media(2)
Austin, TX, USA(1)
Kumamoto, Japan(1)
Philadelphia, PA, USA(1)
Hybrid System(4)
System Dynamics(3)
Trajectory Optimization(3)
Backward Pass(2)
Constraint Forces(2)

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Hybrid iLQR Model Predictive Control for Contact Implicit Stabilization on Legged Robots

Nathan J. Kong;Chuanzheng Li;George Council;Aaron M. Johnson

IEEE Transactions on Robotics

Year: 2023 | Volume: 39, Issue: 6 | Journal Article |

Cited by: Papers (18)

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Model predictive control (MPC) is a popular strategy for controlling robots but is difficult for systems with contact due to the complex nature of hybrid dynamics. To implement MPC for systems with contact, dynamic models are often simplified or contact sequences fixed in time in order to plan trajectories efficiently. In this work, we propose the hybrid iterative linear quadratic regulator (iLQR)...Show More

Hybrid iLQR Model Predictive Control for Contact Implicit Stabilization on Legged Robots

Nathan J. Kong;Chuanzheng Li;George Council;Aaron M. Johnson

IEEE Transactions on Robotics

Year: 2023 | Volume: 39, Issue: 6 | Journal Article |

Hybrid Event Shaping to Stabilize Periodic Hybrid Orbits

James Zhu;Nathan J. Kong;George Council;Aaron M. Johnson

2022 International Conference on Robotics and Automation (ICRA)

Year: 2022 | Conference Paper |

Cited by: Papers (6)

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Many controllers for legged robotic systems leverage open- or closed-loop control at discrete hybrid events to enhance stability. These controllers appear in several well studied phenomena such as the Raibert stepping controller, paddle juggling, and swing leg retraction. This work introduces hybrid event shaping (HES): a generalized method for analyzing and designing stable hybrid event controlle...Show More

Hybrid Event Shaping to Stabilize Periodic Hybrid Orbits

James Zhu;Nathan J. Kong;George Council;Aaron M. Johnson

2022 International Conference on Robotics and Automation (ICRA)

Year: 2022 | Conference Paper |

iLQR for Piecewise-Smooth Hybrid Dynamical Systems

Nathan J. Kong;George Council;Aaron M. Johnson

2021 60th IEEE Conference on Decision and Control (CDC)

Year: 2021 | Conference Paper |

Cited by: Papers (13)

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Trajectory optimization is a popular strategy for planning trajectories for robotic systems. However, many robotic tasks require changing contact conditions, which is difficult due to the hybrid nature of the dynamics. The optimal sequence and timing of these modes are typically not known ahead of time. In this work, we extend the Iterative Linear Quadratic Regulator (iLQR) method to a class of pi...Show More

iLQR for Piecewise-Smooth Hybrid Dynamical Systems

Nathan J. Kong;George Council;Aaron M. Johnson

2021 60th IEEE Conference on Decision and Control (CDC)

Year: 2021 | Conference Paper |

Deadbeat control with (almost) no sensing in a hybrid model of legged locomotion

George Council;Shiyi Yang;Shai Revzen

Proceedings of the 2014 International Conference on Advanced Mechatronic Systems

Year: 2014 | Conference Paper |

Cited by: Papers (8)

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Hybrid systems often appear as models of mechatronic devices, and are used to express the discontinuous transition in dynamics that occurs when mechanical contacts are made or broken. Contact state changes can coincide with dramatic shifts in control authority, and become sources of unwanted disturbance when they are exogenously driven. In the natural world, such systems appear in rapid legged loc...Show More

Deadbeat control with (almost) no sensing in a hybrid model of legged locomotion

George Council;Shiyi Yang;Shai Revzen

Proceedings of the 2014 International Conference on Advanced Mechatronic Systems

Year: 2014 | Conference Paper |

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