Economy vision

IF 2.9 Q2 ROBOTICS
Anton T.J.M. Smals
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引用次数: 1

Abstract

Part manipulation by a robot is practicable provided the orientation of the presented part is known. Traditionally, a multi-part feeder will consist of either a number of dedicated feeders or else of plain feeders equipped with sophisticated electronics. The development of an inexpensive feeder with an uncomplicated recognizing device might be a good alternative. Two recognizing devices of this kind are described. One device includes a moving belt, 3 sensors, and a programmable logic controller, but the device is dedicated to one particular part. The other device consists of a moving belt, 16 sensors, and a microcomputer. This device has self-learning capability. Both devices are able to offer information about the orientation of the part that will be presented to a robot.

经济的愿景
只要所呈现的零件的方向已知,机器人的零件操作是可行的。传统上,多部分馈线将由许多专用馈线或其他配备复杂电子设备的普通馈线组成。开发具有简单识别装置的廉价馈线可能是一个很好的选择。描述了两种这种类型的识别装置。一个设备包括一个移动带,3个传感器和一个可编程逻辑控制器,但该设备专用于一个特定的部分。另一种装置由一条移动带、16个传感器和一台微型计算机组成。该设备具有自学习能力。这两种设备都能够提供有关将呈现给机器人的部件方向的信息。
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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来源期刊
Robotics
Robotics Mathematics-Control and Optimization
CiteScore
6.70
自引率
8.10%
发文量
114
审稿时长
11 weeks
期刊介绍: Robotics publishes original papers, technical reports, case studies, review papers and tutorials in all the aspects of robotics. Special Issues devoted to important topics in advanced robotics will be published from time to time. It particularly welcomes those emerging methodologies and techniques which bridge theoretical studies and applications and have significant potential for real-world applications. It provides a forum for information exchange between professionals, academicians and engineers who are working in the area of robotics, helping them to disseminate research findings and to learn from each other’s work. Suitable topics include, but are not limited to: -intelligent robotics, mechatronics, and biomimetics -novel and biologically-inspired robotics -modelling, identification and control of robotic systems -biomedical, rehabilitation and surgical robotics -exoskeletons, prosthetics and artificial organs -AI, neural networks and fuzzy logic in robotics -multimodality human-machine interaction -wireless sensor networks for robot navigation -multi-sensor data fusion and SLAM
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