基于人体运动的训练和执行机器人系统,具有工业应用原型

Syed Jaad-ul-Haque, M. Talha, Muhammad Faizan Salim, Midhat Ali, Vijay Kumar Khatri, Ahsan Javed Ghangro
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引用次数: 0

摘要

如果机器人必须执行各种任务,则需要对机器人进行频繁的再培训。人类运动是训练机器人最自然、最流畅的输入形式,而机器人运动总是以一种不自然的方式被编程。提出了一种通过实时仿真人体不同肢体运动来训练机器人的方法。人体运动数据也被记录下来,运动可以在以后的时间再生。目的是弥合人类运动和机器人运动之间的差距,使其更自然,并将其应用于基于图像处理的工业分类/检测系统的原型。Lego Mindstorms NXT机器人套件作为机器人使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human motion based training & execution robotic system with a prototype industrial application
Frequent robot re-training is required if the robot has to perform variety of tasks. Human Motion is the most natural and fluent form of input to train a robot, and robot motion has always been programmed in an un-natural way. This paper presents a method of training of robots by real time emulation of human motion of different limbs. The Human Motion data is also recorded and the motion can be regenerated at a later time. The purpose is to bridge the gap between human motion and robotic motion and make it more natural and apply it on a prototype of an Image Processing based Industrial Sorting/Inspection System. Lego Mindstorms NXT Robotic kit is used as the robot.
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