Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Real-Time Trajectory Generation Using Model Predictive Control

Ghazaei, Mahdi LU ; Olofsson, Björn LU ; Robertsson, Anders LU and Johansson, Rolf LU orcid (2015) IEEE International Conference on Automation Science and Engineering (IEEE CASE 2015) p.942-948
Abstract
The problem of planning a trajectory for robots starting in an initial state and reaching a final state in a desired interval of time is tackled. We consider Model Predictive Control as an approach to the problem of point-to-point trajectory generation. We use the developed strategy to generate trajectories for transferring the state of the robot, fulfilling computational real-time requirements. Experiments on an industrial robot in a ball-catching scenario show the effectiveness of the approach.
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2015 IEEE Conference on Automation Science and Engineering (CASE) : Automation for a Sustainable Future - Automation for a Sustainable Future
pages
942 - 948
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE International Conference on Automation Science and Engineering (IEEE CASE 2015)
conference dates
2015-08-24 - 2015-08-28
external identifiers
  • scopus:84952767139
project
PRACE
RobotLab LTH
SMErobotics
language
English
LU publication?
yes
additional info
[Finalist for Best Student Paper Award]
id
719dec89-76c5-44a4-8ae2-108a77964a80 (old id 7856566)
date added to LUP
2016-04-04 13:15:29
date last changed
2023-04-06 17:56:01
@inproceedings{719dec89-76c5-44a4-8ae2-108a77964a80,
  abstract     = {{The problem of planning a trajectory for robots starting in an initial state and reaching a final state in a desired interval of time is tackled. We consider Model Predictive Control as an approach to the problem of point-to-point trajectory generation. We use the developed strategy to generate trajectories for transferring the state of the robot, fulfilling computational real-time requirements. Experiments on an industrial robot in a ball-catching scenario show the effectiveness of the approach.}},
  author       = {{Ghazaei, Mahdi and Olofsson, Björn and Robertsson, Anders and Johansson, Rolf}},
  booktitle    = {{2015 IEEE Conference on	Automation Science and Engineering (CASE) : Automation  for	  a Sustainable	  Future}},
  language     = {{eng}},
  month        = {{08}},
  pages        = {{942--948}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Real-Time Trajectory Generation Using Model Predictive Control}},
  url          = {{https://lup.lub.lu.se/search/files/8475064/8053862.pdf}},
  year         = {{2015}},
}