Constrained multi-objective trajectory planning of parallel kinematic machines

  • Amar Khoukhi*
  • , Luc Baron
  • , Marek Balazinski
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

50 Scopus citations

Abstract

This paper presents a new approach to multi-objective dynamic trajectory planning of parallel kinematic machines (PKM) under task, workspace and manipulator constraints. The robot kinematic and dynamic model, (including actuators) is first developed. Then the proposed trajectory planning system is introduced. It minimizes electrical and kinetic energy, robot traveling time separating two sampling periods, and maximizes a measure of manipulability allowing singularity avoidance. Several technological constraints such as actuator, link length and workspace limitations, and some task requirements, such as passing through imposed poses are simultaneously satisfied. The discrete augmented Lagrangean technique is used to solve the resulting strong nonlinear constrained optimal control problem. A decoupled formulation is proposed in order to cope with some difficulties arising from dynamic parameters computation. A systematic implementation procedure is provided along with some numerical issues. Simulation results proving the effectiveness of the proposed approach are given and discussed.

Original languageEnglish
Pages (from-to)756-769
Number of pages14
JournalRobotics and Computer-Integrated Manufacturing
Volume25
Issue number4-5
DOIs
StatePublished - Aug 2009

Bibliographical note

Funding Information:
Amar Khoukhi received his Ph.D. degree in Mechanical Engineering from Mechanical Engineering Dept, University of Montreal in 2007, an Engineering Doctorate from Software Engineering Dept. of National School of Telecommunication Engineers, Paris, France, in 1991 and an Advanced Diploma of University Studies in Operation Research from Decision Mathematics Institute of University Paris IX Dauphine in 1985. Over the last several years, he had been actively involved in several research projects in the fields of robotics, soft computing and applied optimization and funded by NSERC Canada, CNRS France and Electricity of France. Since February 2008, he joined Systems Engineering Dept. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia. He received the Best Paper Award at NAFIPS’2007 Conference held at San Diego, CA, June 25–27, 2007 and has published more than 40 international peer-reviewed journal papers and over 90 conference papers. His research interests include robotics, applied optimization and intelligent systems.

Funding Information:
The authors gratefully thank the Natural Science and Engineering Research Council of Canada (NSERC) for supporting this work under Grants ES D3-317622, RGPIN-203618, RGPIN-105518 and STPGP-269579. The first author thanks also King Fahd University of Petroleum and Minerals for general support.

Keywords

  • Augmented lagrangean
  • Constrained off-line programming
  • Decoupling
  • Nonlinear optimal control
  • Parallel kinematic machines
  • Time-energy trajectory planning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • General Mathematics
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Fingerprint

Dive into the research topics of 'Constrained multi-objective trajectory planning of parallel kinematic machines'. Together they form a unique fingerprint.

Cite this