TY - GEN
T1 - An Improved neurocomputation scheme for minimum infinity-norm kinematic control of redundant manipulators
AU - Tang, Wai Sum
AU - Wang, Jun
PY - 1999/7
Y1 - 1999/7
N2 - This paper presents an improved neural computation scheme for kinematic control of redundant manipulators based on infinity-norm joint velocity minimization. Compared with a previous neural network approach to minimum infinity-norm kinematic control, the presented approach has a less complex architecture. The recurrent neural network explicitly minimizes the maximum component of the joint velocity vector while tracking a desired end-effector trajectory. The end-effector velocity vector for a given task is fed into the neural network from its input and the minimum infinity-norm joint velocity vector is generated at its output instantaneously. Analytical results are given to substantiate the asymptotic stability of the recurrent neural network. The simulation results of a four degree-of-freedom planar robot arm are presented to show the proposed neural network can effectively compute the minimum infinity-norm solution to redundant manipulators in real-time. © 1999 IEEE
AB - This paper presents an improved neural computation scheme for kinematic control of redundant manipulators based on infinity-norm joint velocity minimization. Compared with a previous neural network approach to minimum infinity-norm kinematic control, the presented approach has a less complex architecture. The recurrent neural network explicitly minimizes the maximum component of the joint velocity vector while tracking a desired end-effector trajectory. The end-effector velocity vector for a given task is fed into the neural network from its input and the minimum infinity-norm joint velocity vector is generated at its output instantaneously. Analytical results are given to substantiate the asymptotic stability of the recurrent neural network. The simulation results of a four degree-of-freedom planar robot arm are presented to show the proposed neural network can effectively compute the minimum infinity-norm solution to redundant manipulators in real-time. © 1999 IEEE
UR - http://www.scopus.com/inward/record.url?scp=0033333603&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0033333603&origin=recordpage
U2 - 10.1109/IJCNN.1999.832692
DO - 10.1109/IJCNN.1999.832692
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 0-7803-5529-6
VL - 3
SP - 2005
EP - 2010
BT - IJCNN '99 - International Joint Conference on Neural Networks
PB - IEEE
T2 - 1999 International Joint Conference on Neural Networks (IJCNN'99)
Y2 - 10 July 1999 through 16 July 1999
ER -