Object recognition based on depth information and associative memory

S. Puls, Norah Schnorr, H. Wörn
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引用次数: 1

Abstract

Steady improvement of robotic systems due to developments in the realm of sensing the world enables advances towards human-robot-cooperation. In order for the robot to be reactive in its environment objects need to be identified. In this paper an approach is presented which allows identification of objects in the working area of an industrial robot. Neural Networks are used as associative memory to learn new items and efficiently recognize learned objects.
基于深度信息和联想记忆的目标识别
由于感知世界领域的发展,机器人系统的稳步改进使人类-机器人合作取得进展。为了使机器人在其环境中做出反应,需要识别物体。本文提出了一种能够识别工业机器人工作区域内物体的方法。神经网络被用作联想记忆来学习新项目,并有效地识别学习过的物体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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