Title :
Parallel robots pose accuracy compensation using artificial neural networks
Author_Institution :
Autom. Coll., Harbin Eng. Univ., Harbin
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;
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
DOI :
10.1109/ICMA.2008.4798850