Hostname: page-component-76fb5796d-25wd4 Total loading time: 0 Render date: 2024-04-29T16:21:55.677Z Has data issue: false hasContentIssue false
  • English
  • Français

Optimal location of a robot path when considering velocity performance

Published online by Cambridge University Press:  09 April 2002

N. A. Aspragathos  and
S. Foussias
N. A. Aspragathos
Affiliation:
Mechanical and Aeronautics Engineering Department, University of Patras, Patras (Greece)asprag@mech.upatras.gr
S. Foussias
Affiliation:
Mechanical and Aeronautics Engineering Department, University of Patras, Patras (Greece)
Get access Rights & Permissions [Opens in a new window]

Abstract

A method for searching the best location of a path in the robot workspace considering the velocity performance of the robot is presented. After a thorough investigation of the robot performance indices, a new measure for the velocity efficiency of a robot moving its end-effector along a path is introduced. This measure is an approximation of the minimum of the Manipulator Velocity Ratio (MVR) along the path. The minimum is calculated from a finite set of MVRs determined at specified points of the path using an algorithm for an approximate motion of the end effector along the path.

The introduced measure is used as the objective function in an optimisation problem, where an optimal location of the path is searched. The objective function is procedural and non continuous, so a Genetic Algorithm is used to search the space for the optimal location of the path. The proposed method is tested using a simulated PUMA-like robot, which has to move its end-effector along a straight-line segment. At the end of the paper, the results obtained in these tests are presented and discussed.

Type
Research Article
Information
Robotica , Volume 20 , Issue 2 , March 2002 , pp. 139 - 147
Copyright
© 2002 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)