Using Quadratic Interpolated Beetle Antennae Search to Enhance Robot Arm Calibration Accuracy

Abstract

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.