在不同机器人平台之间传递物体抓取知识和技能

A. Paikan, David Schiebener, Mirko Wächter, T. Asfour, G. Metta, L. Natale
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引用次数: 8

摘要

本研究描述了两种不同的类人机器人在不同软件框架下抓取物体技能的迁移。我们在仿人机器人iCub和ARMAR-III之间实现了这样的知识和技能转移。这两种机器人具有不同的运动学,并使用不同的中间件YARP和ArmarX进行编程。我们开发了一个桥接系统,允许在iCub上执行ARMAR-III的抓取技能。由于实施例的不同,一个机器人的已知可行抓取对于另一个机器人并不总是可行的。我们提出了一种反应性纠正行为来检测抓取执行过程中的故障,并对其进行纠正,直到抓取成功,从而使已知的抓取定义适应新的实施例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transferring object grasping knowledge and skill across different robotic platforms
This study describes the transfer of object grasping skills between two different humanoid robots with different software frameworks. We realize such a knowledge and skill transfer between the humanoid robots iCub and ARMAR-III. These two robots have different kinematics and are programmed using different middlewares, YARP and ArmarX. We developed a bridge system to allow for the execution of grasping skills of ARMAR-III on iCub. As the embodiment differs, the known feasible grasps for the one robot are not always feasible for the other robot. We propose a reactive correction behavior to detect failure of a grasp during its execution, to correct it until it is successful, and thus adapt the known grasp definition to the new embodiment.
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