安装在工业机器人末端的串联力传感器数值补偿方法研究

Zhijian Zhang, Youping Chen, Dailin Zhang, Qi Tong
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引用次数: 1

摘要

串联力传感器是人机协作和演示学习中的重要传感器,机器人可以同时感知环境状态和人的注意力。串联式力传感器的姿态随机器人姿态的变化而变化,导致传感器的输出不能准确反映环境状态和人的意图。为了补偿姿态变化引起的测量误差,提出了基于深度学习的串联力传感器数值补偿方法。数值补偿实验结果表明,该方法能有效消除姿态变化对传感器测量的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on numerical compensation method of tandem force sensor installed at the end of industrial robot
Tandem force sensor is an important sensor in human-robot collaboration and learning from demonstration, equipped with which robot can perceive the environment state and human attention simultaneously. The posture of a tandem force sensor changes with robot’s posture, which leads to the output of the sensor cannot accurately reflect the environmental states and human intention. In order to compensate the measurement error caused by attitude change, the numerical compensation method of tandem force sensor based on deep learning is proposed in this paper. And the experimental results of numerical compensation show that this method can effectively eliminate the influence of attitude change on the measurement of the sensor.
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