@inproceedings{a2157fe992254cf6a7318b14b127ad60,
title = "Complete calibration of industrial robot with limited parameters and neural network",
abstract = "Poor accuracy of industrial robots cannot meet the requirements of some high precision assignments, especially in heavy load condition. Geometric errors and joint compliances are mainly responsible for this poor accuracy. This paper presents a complete calibration method considering geometric errors, joint compliances and exterior load. An integrated inverse kinematics algorithm combining neural network and analytical method is proposed to calculate controller angle inputs in calibration. For the convenience of calculation, limited parameters calibration is used and then simulated in Matlab. As experimental validation on ABB IRB 6640 shows, the proposed complete calibration model based on limited parameters and neural network can dramatically improve the positioning accuracy of industrial robot.",
keywords = "calibration, industrial robot, inverse kinematics, limited parameters, neural network",
author = "Wang Xu and Li Dongsheng and Wang Mingming",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 4th IEEE International Symposium on Robotics and Intelligent Sensors, IRIS 2016 ; Conference date: 17-12-2016 Through 20-12-2016",
year = "2017",
month = oct,
day = "11",
doi = "10.1109/IRIS.2016.8066074",
language = "英语",
series = "IRIS 2016 - 2016 IEEE 4th International Symposium on Robotics and Intelligent Sensors: Empowering Robots with Smart Sensors",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "103--108",
booktitle = "IRIS 2016 - 2016 IEEE 4th International Symposium on Robotics and Intelligent Sensors",
address = "美国",
}