Redundancy resolution of robotic manipulators with neural computation

Author

Ding, H. ; Tso, S.K.

Author_Institution

Centre for Intelligent Design, Autom. & Manuf., City Univ. of Hong Kong, Kowloon, Hong Kong

Volume

46

Issue

1

fYear

1999

fDate

2/1/1999 12:00:00 AM

Firstpage

230

Lastpage

233

Abstract

This letter presents a neural-network-based computational scheme for redundancy resolution of manipulators. The Tank-Hopfield (TH) network is adopted for pseudoinverse and inverse kinematics calculations and it can provide joint velocity and joint acceleration solutions within a time frame of the order of hundreds of nanoseconds. Incorporating the TH network into the redundancy resolution scheme allows planning algorithms to be implemented in real time. Simulation results for a three-link planar manipulator are presented to demonstrate that the proposed approach is efficient and practical

Keywords

Hopfield neural nets; control system analysis; control system synthesis; manipulator kinematics; neurocontrollers; redundant manipulators; Tank-Hopfield network; control design; control simulation; inverse kinematics calculations; joint acceleration; joint velocity; neural computation; planning algorithms; pseudoinverse kinematics calculations; redundancy resolution; robotic manipulators; three-link planar manipulator; Acceleration; Design automation; Equations; Jacobian matrices; Kinematics; Manipulator dynamics; Manufacturing automation; Neural networks; Optimization methods; Robots;

fLanguage

English

Journal_Title

Industrial Electronics, IEEE Transactions on

Publisher

ieee

ISSN

0278-0046

Type

jour

DOI

10.1109/41.744418

Filename

744418