TY  - JOUR
AB  - Purpose This paper aims to provide a simple and flexible calibration method of parallel manipulators for improving the position accuracy only using partial pose information.Design/methodology/approach The overall idea of this method is to use BP neural network to fit the relationship between calibration parameters and measurement parameters and then adjust calibration parameters according to measurements.Findings The calibration method significantly improves the position accuracy of the six-axis parallel manipulator. Simulation shows that the accuracy can be improved by increasing the number of positions consisted of samples to train BP neural network, and when the position number is increased, the descent velocity of fitting error is decreased.Originality/value The method is general for various parallel mechanisms and simple for measurement process. It can be applied to the calibration of various mechanisms without analyzing the mathematical relationship between measurements and calibration parameters. The measurement parameters can be flexibly selected to simplify measurement process, which saves calibration cost and time.
VL  - 46
IS  - 5
SN  - 0143-991X
DO  - 10.1108/IR-12-2018-0248
UR  - https://doi.org/10.1108/IR-12-2018-0248
AU  - Zhang Dianjin
AU  - Zhang Guangyu
AU  - Li Longqiu
PY  - 2019
Y1  - 2019/01/01
TI  - Calibration of a six-axis parallel manipulator based on BP neural network
T2  - Industrial Robot: the international journal of robotics research and application
PB  - Emerald Publishing Limited
SP  - 692
EP  - 698
Y2  - 2024/09/19
ER  -