DocumentCode
2960794
Title
Parallel robots pose accuracy compensation using artificial neural networks
Author
Yu, Da-yong
Author_Institution
Autom. Coll., Harbin Eng. Univ., Harbin
fYear
2008
fDate
5-8 Aug. 2008
Firstpage
750
Lastpage
754
Abstract
Parallel robots pose accuracy compensation approach using artificial neural networks has been developed. In this method, an artificial neural network is used with conventional inverse kinematics computation module in parallel. A back propagation neural network is designed and implemented to learn parallel robot kinematics model error. The trained neural network can be used to performed on-line pose accuracy compensation in task. Simulation and experimental results for a parallel robot are presented to show the effectiveness of the compensation method based on neural networks.
Keywords
neurocontrollers; robot kinematics; accuracy compensation approach; artificial neural networks; backpropagation neural network; compensation method; inverse kinematics computation module; parallel robots pose accuracy compensation; Artificial neural networks; Biological neural networks; Calibration; Computer networks; Concurrent computing; Orbital robotics; Parallel robots; Predictive models; Robot kinematics; Robotics and automation; Parallel robot; accuracy compensation; artificial neural networks; kinematics calibration; pose accuracy;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronics and Automation, 2008. ICMA 2008. IEEE International Conference on
Conference_Location
Takamatsu
Print_ISBN
978-1-4244-2631-7
Electronic_ISBN
978-1-4244-2632-4
Type
conf
DOI
10.1109/ICMA.2008.4798850
Filename
4798850
Link To Document