Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-14T18:33:18.128Z Has data issue: false hasContentIssue false

Task planning for serial redundant manipulators

Published online by Cambridge University Press:  01 January 1997

J. A. Kuo
Affiliation:
Research Institute for Design, Manufacture and Marketing, University of Salford, Salford M5 4WT, UK. Tel: +44(0)161 745 5105, Fax: +44(0)161 745 5040. E-mail: d.j.sanger@aeromech.slaford.ac.uk
D. J. Sanger
Affiliation:
Research Institute for Design, Manufacture and Marketing, University of Salford, Salford M5 4WT, UK. Tel: +44(0)161 745 5105, Fax: +44(0)161 745 5040. E-mail: d.j.sanger@aeromech.slaford.ac.uk

Abstract

The first stage in developing a task planning language for redundant manipulators is that of constructing an algorithm to produce a schedule of joint displacements for the specified task. This algorithm may be based upon the use of an inverse infinitesimal kinematic analysis for the majority of the path with a finite inverse analysis used to provide an initial joint configuration and periodically to correct for any joint errors that may have accumulated. Here, it is assumed that there is complete correlation and coherence of solutions between these analyses, otherwise problems, such as a lack of repeatability may occur. This may be accomplished by modelling the manipulator as an elastic system which permits the development of a task planning method by using analyses which are all mutually coherent. In this paper, the method is developed and demonstrated using a redundant manipulator that simultaneously avoids obstables, singularities and joint motion limitations. The task planning method and associated analyses are applicable to the general serial redundant manipulator with an arbitrary degree of redundancy.

Type
Research Article
Copyright
© 1997 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.)