QP-Based Visual Servoing Under Motion Blur-Free Constraint

被引：0

作者：

Robic, Maxime ^{[1
]}

Fraisse, Renaud ^{[2
]}

Marchand, Eric ^{[1
]}

Chaumette, Francois ^{[1
]}

机构：

[1] Univ Rennes, CNRS, IRISA, Inria, F-35042 Rennes, France

[2] Airbus Def & Space, F-31400 Toulouse, France

来源：

IEEE ROBOTICS AND AUTOMATION LETTERS | 2024年 / 9卷 / 10期

关键词：

Cameras; Satellites; Visualization; Visual servoing; Task analysis; Earth; Target tracking; space robotics and automation; visual tracking; IMAGE GRADIENT; IDENTIFICATION;

D O I：

10.1109/LRA.2024.3451394

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

This letter proposes a QP-based visual servoing scheme for limiting motion blur during the achievement of a visual task. Unlike traditional image restoration approaches, we want to avoid any deconvolution step by keeping the image sequence acquired by the camera as sharp as possible. To do so, we select the norm of the image gradient as sharpness metric, from which we design a velocity constraint that is injected in a QP controller. Our system is evaluated for an Earth observation satellite. Simulation and experimental results show the effectiveness of our approach.

引用

页码：8738 / 8745

页数：8

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