Open AccessRobot Dynamic Parameter Identification based on BBO Algorithm
Author(s) -
Yu-xuan Xu,
Shao-yu Ke
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1237/2/022187
Subject(s) - robot , computer science , algorithm , constraint (computer aided design) , trajectory , genetic algorithm , fourier series , identification (biology) , calibration , matrix (chemical analysis) , series (stratigraphy) , torque , control theory (sociology) , artificial intelligence , mathematics , machine learning , control (management) , mathematical analysis , paleontology , statistics , physics , geometry , botany , materials science , astronomy , composite material , biology , thermodynamics
In this paper, a linearized robot dynamics model is first established. The DH parameters and physical constraints of the robot are given. The joint motion trajectory based on Fourier series is designed then. By setting the conditional number of the observation matrix as the objective function, an Biogeography-based optimization algorithm is applied to identify the dynamic parameters of the robot. The physical constraint calibration and predictive torque results are compared with the traditional genetic algorithm to verify the advanced nature of our method.