CLC number: TP242.6
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2012-07-06
Cited: 4
Clicked: 11159
Hao-jie Zhang, Jian-wei Gong, Yan Jiang, Guang-ming Xiong, Hui-yan Chen. An iterative linear quadratic regulator based trajectory tracking controller for wheeled mobile robot[J]. Journal of Zhejiang University Science C, 2012, 13(8): 593-600.
@article{title="An iterative linear quadratic regulator based trajectory tracking controller for wheeled mobile robot",
author="Hao-jie Zhang, Jian-wei Gong, Yan Jiang, Guang-ming Xiong, Hui-yan Chen",
journal="Journal of Zhejiang University Science C",
volume="13",
number="8",
pages="593-600",
year="2012",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1100379"
}
%0 Journal Article
%T An iterative linear quadratic regulator based trajectory tracking controller for wheeled mobile robot
%A Hao-jie Zhang
%A Jian-wei Gong
%A Yan Jiang
%A Guang-ming Xiong
%A Hui-yan Chen
%J Journal of Zhejiang University SCIENCE C
%V 13
%N 8
%P 593-600
%@ 1869-1951
%D 2012
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1100379
TY - JOUR
T1 - An iterative linear quadratic regulator based trajectory tracking controller for wheeled mobile robot
A1 - Hao-jie Zhang
A1 - Jian-wei Gong
A1 - Yan Jiang
A1 - Guang-ming Xiong
A1 - Hui-yan Chen
J0 - Journal of Zhejiang University Science C
VL - 13
IS - 8
SP - 593
EP - 600
%@ 1869-1951
Y1 - 2012
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1100379
Abstract: We present an iterative linear quadratic regulator (ILQR) method for trajectory tracking control of a wheeled mobile robot system. The proposed scheme involves a kinematic model linearization technique, a global trajectory generation algorithm, and trajectory tracking controller design. A lattice planner, which searches over a 3D (x, y, θ) configuration space, is adopted to generate the global trajectory. The ILQR method is used to design a local trajectory tracking controller. The effectiveness of the proposed method is demonstrated in simulation and experiment with a significantly asymmetric differential drive robot. The performance of the local controller is analyzed and compared with that of the existing linear quadratic regulator (LQR) method. According to the experiments, the new controller improves the control sequences (v, ω) iteratively and produces slightly better results. Specifically, two trajectories, ‘S’ and ‘8’ courses, are followed with sufficient accuracy using the proposed controller.
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