Penalty approach for a constrained optimization to solve on-line the inverse kinematic problem of redundant manipulators

In this paper, a penalty approach which deals with a constrained optimization to solve the inverse kinematic of redundant robot manipulators is considered. An optimization procedure using neural networks is formulated, it produces on-line position and velocity trajectories in joint space from positi...

Full description

Saved in:
Bibliographic Details
Published inProceedings of IEEE International Conference on Robotics and Automation Vol. 1; pp. 133 - 138 vol.1
Main Authors Ramdane-Cherif, A., Perdereau, V., Drouin, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Constraint optimization
Jacobian matrices
Manipulators
Minimization methods
Neural networks
Null space
Optimal control
Orbital robotics
Robot kinematics
Trajectory
Online AccessGet full text
ISBN0780329880
9780780329881
ISSN1050-4729
DOI10.1109/ROBOT.1996.503585

Cover

More Information
Summary:In this paper, a penalty approach which deals with a constrained optimization to solve the inverse kinematic of redundant robot manipulators is considered. An optimization procedure using neural networks is formulated, it produces on-line position and velocity trajectories in joint space from position and orientation trajectories in Cartesian space. This new method offers substantially better accuracy and guarantees a good minimization of a performance function subject to joint limitations while achieving the end-effector task.
ISBN:0780329880
9780780329881
ISSN:1050-4729
DOI:10.1109/ROBOT.1996.503585