DocumentCode :
2776757
Title :
Coordination of Two Redundant Robots Using a Dual Neural Network
Author :
Hou, Zeng-Guang ; Cheng, Long ; Tan, Min
Author_Institution :
Laboratory of Complex Systems and Intelligence Science, Institution of Automation, Chinese Academy of Sciences, P. O. Box 2728, Beijing 100080, China. zengguang.hou@ia.ac.cn
fYear :
2006
fDate :
16-21 July 2006
Firstpage :
4187
Lastpage :
4192
Abstract :
Real-time control of multi-robot coordination system has attracted a lot of attention in recent years. Traditional numerical algorithm is ineffective to perform this task. In this paper, a dual neural network approach is applied to resolve the coordination problem of two redundant robots. By this approach, the joint torque and distributed load can be obtained by optimizing a multiple criteria, and the physical limits of the joint torque and distributed load can be also incorporated into the control scheme. The dual neural network has a simple structure which is composed of only one layer of neuron array. The network configuration is updated by the command signals of desired acceleration of the grasped object, and the output of the network is the manipulator´s joint torque. A simulation example is presented to demonstrate the effectiveness of the dual neural network method.
Keywords :
Redundant robots; coordination manipulation; dual neural network; Automatic control; Force control; Force feedback; Linear feedback control systems; Neural networks; Optimal control; Robot kinematics; Robotic assembly; Robotics and automation; Torque control; Redundant robots; coordination manipulation; dual neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Print_ISBN :
0-7803-9490-9
Type :
conf
DOI :
10.1109/IJCNN.2006.246968
Filename :
1716677
Link To Document :
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