Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-22T03:48:44.615Z Has data issue: false hasContentIssue false

Optimal path planning of manipulatory systems subjected tonon-autonomous motion laws

Published online by Cambridge University Press:  01 May 1997

A. D. Jutard-Malinge
Affiliation:
Université de Poitiers, Laboratoire de Mécanique des Solides (URA-CNRS 861), S.P.2M.I, Bd. 3, Téléport 2, BP 179, 86960 Futuroscope Cedex, France
G. Bessonnet
Affiliation:
Université de Poitiers, Laboratoire de Mécanique des Solides (URA-CNRS 861), S.P.2M.I, Bd. 3, Téléport 2, BP 179, 86960 Futuroscope Cedex, France

Abstract

A path planning method is presented based on non-autonomous dynamicmodeling of open-loops in articulated systems. It is assumed that one part ofthe mechanical system is submitted to specified motions laws, while movements ofthe complementary part are free. Thus, motion optimization is related to freejoint movements but it is achieved on the basis of the dynamic model of thewhole mechanical system. This approach introduces a non-autonomous stateequation of a special type in the sense that it can not only depend on therunning time but also on the unknown travelling time. The cost function to beminimized involves the travelling time and the actuating inputs. Optimization isachieved by applying the Pontryagin Maximum Principle which yields a newoptimality condition concerning the travelling time dependency of the statedproblem. Two simulation examples are presented. The first one shows how thedeveloped technique makes possible both the reducing and mastering the dynamiccomplexity of a four degrees of freedom-vertical manipulator. Set at fourdegrees of freedom, the second one deals with a redundant planar manipulatorcharacterized by a mobile base that is submitted to a specified drivingmotion.

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.)