Eye-in-Hand Visual Servoing Control of Robot Manipulators Based on an Input Mapping Method

被引：14
|
作者：
He, Shaoying [1 ]
Xu, Yunwen [1 ]
Li, Dewei [1 ]
Xi, Yugeng [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
来源：
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY | 2023年 / 31卷 / 01期
基金：
美国国家科学基金会; 中国博士后科学基金;
关键词：
Jacobian matrices; Visual servoing; Cameras; Robots; Manipulators; Robot kinematics; Uncertainty; Input mapping method; output-input data; parametric uncertainties; visual servo control; TRACKING; FEATURES;
D O I：
10.1109/TCST.2022.3172571
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In image-based visual servoing (IBVS), parametric uncertainties tend to cause the model inaccuracy and limit the control performance. Considering these uncertainties can be embodied by the output-input data from the visual servoing system, this brief proposes an eye-in-hand visual servoing control (VSC) scheme based on the input mapping method, which directly utilizes the past output-input data to enhance the original feedback control law rather than identifying the model. The system with the input mapping method is proven to not only maintain the stability of the original VSC but also accelerate the convergent rate. The results of the experiments on a manipulator with an eye-in-hand camera demonstrate the superiority of our proposed method.
引用
收藏
页码：402 / 409
页数：8
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