Paper Info
Title
A Velocity-Level Bi-Criteria Optimization Scheme for Coordinated Path Tracking of Dual Robot Manipulators Using Recurrent Neural Network.
Abstract
A dual-robot system is a robotic device composed of two robot arms. To eliminate the joint-angle drift and prevent the occurrence of high joint velocity, a velocity-level bi-criteria optimization scheme, which includes two criteria (i.e., the minimum velocity norm and the repetitive motion), is proposed and investigated for coordinated path tracking of dual robot manipulators. Specifically, to realize the coordinated path tracking of dual robot manipulators, two subschemes are first presented for the left and right robot manipulators. After that, such two subschemes are reformulated as two general quadratic programs (QPs), which can be formulated as one unified QP. A recurrent neural network (RNN) is thus presented to solve effectively the unified QP problem. At last, computer simulation results based on a dual three-link planar manipulator further validate the feasibility and the efficacy of the velocity-level optimization scheme for coordinated path tracking using the recurrent neural network.
Year
DOI
Venue
2017
10.3389/fnbot.2017.00047
FRONTIERS IN NEUROROBOTICS
Keywords
Field
DocType
dual robot manipulators,bi-criteria optimization scheme,recurrent neural network,quadratic program,repetitive motion
Mathematical optimization,Planar manipulator,Computer science,Control theory,Quadratic equation,Recurrent neural network,Artificial intelligence,Quadratic programming,Robot manipulator,Robot,Path tracking,Machine learning
Journal
Volume
ISSN
Citations 
11
1662-5218
1
PageRank 
References 
Authors
0.36
33
6
Name
Order
Citations
PageRank
Lin Xiao156242.84
Yongsheng Zhang220443.58
Bolin Liao328118.70
Zhijun Zhang428631.45
Lei Ding514226.77
Long Jin653728.68