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Stereo vision-based object classification

机译:基于立体视觉的对象分类

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摘要

A novel concept for recognition and classification of differently formed objects is introduced. It can be used for manipulating objects by uncalibrated vision-guided manipulators. The object recognition is achieved according to an object-oriented and model-based approach. The task is decomposed into several largely independent modules, and each module is responsible for a limited subtask. The emphasis in this article is on the object classification. It is achieved by observing directly the object appearance in real-time images without precise quantitative knowledge about the manipulated objects. The approach was evaluated and demonstrated in real-word experiments on an uncalibrated vision-guided manipulator with five degrees of freedom for recognition, classification and manipulation of a variety of differently shaped objects in nearly arbitrary orientations and positions anywhere in the robot's 3D work space.
机译:引入了一种新颖的概念,用于识别和分类不同形式的物体。它可以用于未经校准的视觉引导操纵器操纵物体。根据面向对象和基于模型的方法来实现对象识别。该任务被分解为几个基本独立的模块,每个模块负责一个有限的子任务。本文的重点是对象分类。它是通过直接观察实时图像中的对象外观而无需有关被操作对象的精确定量知识来实现​​的。该方法已在具有五个自由度的未经校准的视觉引导操纵器的真实单词实验中进行了评估并得到了证明,可在机器人3D工作空间中的任意位置和位置以几乎任意方向识别,分类和操纵各种不同形状的物体。

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