Solution of inverse kinematics problems of a highly kinematically redundant manipulator using genetic algorithms

This paper investigates using genetic algorithms (GAs) to solve the inverse kinematics problem for a manipulator with high kinematic redundancy. This is a global nonlinear constrained optimisation problem which involves searching for a set of manipulator joint positions to place the end effector at...

Full description

Saved in:
Bibliographic Details
Main Authors: Buckley, K.A, Hopkins, S.H, Turton, B.C.H
Format: Conference Proceeding
Language:English
Subjects:
Algorithmics. Computability. Computer arithmetics
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Control system analysis and synthesis methods
Exact sciences and technology
Manipulators
Operational research and scientific management
Operational research. Management science
Optimisation techniques
Problem solving, game playing
Scheduling, sequencing
Theoretical computing
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper investigates using genetic algorithms (GAs) to solve the inverse kinematics problem for a manipulator with high kinematic redundancy. This is a global nonlinear constrained optimisation problem which involves searching for a set of manipulator joint positions to place the end effector at a specified position and orientation. The problem is complicated by the presence of obstacles that limit the postures available. The problem is first attempted using a traditional blind GA. It is then shown that performance can be improved by enhancing the GA with heuristics based on knowledge of manipulator kinematics and by prolonging diversity in the GA.
ISSN:0537-9989
DOI:10.1049/cp:19971191