  Over the past decades, industrial manipulators play a vital role in in
various fields, like aircraft manufacturing and automobile manufacturing.
However, an industrial manipulator without calibration suffers from its low
absolute positioning accuracy, which extensively restricts its application in
high-precision intelligent manufacture. Recent manipulator calibration methods
are developed to address this issue, while they frequently encounter long-tail
convergence and low calibration accuracy. To address this thorny issue, this
work proposes a novel manipulator calibration method incorporating an extended
Kalman filter with a Quadratic Interpolated Beetle Antennae Search algorithm.
This paper has three-fold ideas: a) proposing a new Quadratic Interpolated
Beetle Antennae Search algorithm to deal with the issue of local optimum and
low convergence rate in a Beetle Antennae Search algorithm; b) adopting an
extended Kalman filter algorithm to suppress non-Gaussian noises and c)
developing a new manipulator calibration method incorporating an extended
Kalman filter with a Quadratic Interpolated Beetle Antennae Search algorithm to
calibrating a manipulator. Extensively experimental results on an ABB IRB120
industrial manipulator demonstrate that the proposed method achieves much
higher calibration accuracy than several state-of-the-art calibration methods.
