Conjugated Visual Predictive Control for Constrained Visual Servoing

被引：8

作者：

Mohammad Hossein Fallah, Mostafa ^{[1
]}

Janabi-Sharifi, Farrokh ^{[2
]}

机构：

[1] Ryerson Univ, Mech & Ind Engn Dept, Toronto, ON, Canada

[2] Ryerson Univ, Fac Engn & Architectural Sci, Mech & Ind Engn Dept, Toronto, ON, Canada

来源：

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS | 2021年 / 101卷 / 02期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Visual servoing; Model predictive control; Hybrid method;

D O I：

10.1007/s10846-020-01299-6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A novel model predictive control scheme for constrained visual servoing is developed. The proposed method compensates the shortcomings of available MPC schemes in visual servoing and can be utilized for positioning robots in uncertain environments with internal and external constrains. The system model is designed by weighted conjugating of the well-known image-based and position-based approaches. The stability analysis of the control scheme is presented and by illustrating several simulations, the performance and robustness of proposed control structure is demonstrated.

引用

页数：21

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