Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)

Kuka Youbot Arm Path Planning Based on Gravity

Authors
Boquan Zhang, Sheng Gao
Corresponding Author
Boquan Zhang
Available Online May 2018.
DOI
10.2991/meees-18.2018.75How to use a DOI?
Keywords
mechanical arm; ROS; Motion control; Trajectory planning; Gravitational potential energy.
Abstract

Aiming at the various algorithms in the mechanical arm trajectory planning, this paper proposes a trajectory planning algorithm based on an open source software platform (ROS) for the control System of the Robot arm. Mechanical arm on the platform, the gravitational potential energy as the optimization criterion, design a kind of optimization algorithm based on polynomial interpolation five times as a planning algorithm, and through the simulation results verify the effectiveness of the improved control algorithm can improve the performance of mechanical arm. This method is of universal guiding significance for the realization of trajectory planning of engineering mechanical arm.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)
Series
Advances in Engineering Research
Publication Date
May 2018
ISBN
978-94-6252-534-4
ISSN
2352-5401
DOI
10.2991/meees-18.2018.75How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Boquan Zhang
AU  - Sheng Gao
PY  - 2018/05
DA  - 2018/05
TI  - Kuka Youbot Arm Path Planning Based on Gravity
BT  - Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)
PB  - Atlantis Press
SP  - 426
EP  - 429
SN  - 2352-5401
UR  - https://doi.org/10.2991/meees-18.2018.75
DO  - 10.2991/meees-18.2018.75
ID  - Zhang2018/05
ER  -