机器人
扩展卡尔曼滤波器
卡尔曼滤波器
校准
计算机科学
机械臂
趋同(经济学)
人工智能
运动学
滤波器(信号处理)
工业机器人
计算机视觉
数学
统计
物理
经典力学
经济
经济增长
作者
Zhibin Li,Shuai Li,Xin Luo
出处
期刊:IEEE robotics and automation letters
日期:2022-10-01
卷期号:7 (4): 12046-12053
被引量:20
标识
DOI:10.1109/lra.2022.3211776
摘要
During the past decades, industrial robot arms have been widely adopted in various fields, like aerospace and medical care. However, an uncalibrated industrial robot arm suffers from its high absolute positioning error, which tremendously restricts its application in high-precision intelligent manufacture. Related robot arm calibration methods present a potential solution to this issue, while recent algorithms frequently encounter some issues, such as long-tail convergence and low calibration accuracy. To address this thorny issue, this study proposes a novel robot arm calibration method incorporating the extended Kalman filter with Quadratic Interpolated Beetle Antennae Search algorithm. It adopts three-fold ideas: a) developing a new Quadratic Interpolated Beetle Antennae Search algorithm that greatly addresses the issue of local optimum and low convergence rate in a Beetle Antennae Search algorithm; b) adopting an extended Kalman filter algorithm to decrease the influence of measurement noises and c) proposing a robot arm calibration method incorporating an extended Kalman filter with Quadratic Interpolated Beetle Antennae Search algorithm to searching the optimal kinematic parameters of a robot arm. Extensive experiments on an ABB IRB120 industrial robot arm demonstrate that the calibration accuracy of the proposed method is 5.17% higher than that of the state-of-the-art method. Therefore, it is appropriate for practical application occasions with high-precision requirements.
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