| Issue |
MATEC Web Conf.
Volume 128, 2017
2017 International Conference on Electronic Information Technology and Computer Engineering (EITCE 2017)
|
|
|---|---|---|
| Article Number | 04001 | |
| Number of page(s) | 7 | |
| Section | Computer Programming | |
| DOI | https://doi.org/10.1051/matecconf/201712804001 | |
| Published online | 25 October 2017 | |
Optimization on Trajectory of Stanford Manipulator based on Genetic Algorithm
School of Mechanical Engineerin, University of Science and Technology Beijing, 100083 Beijing, China
a Corresponding author: hanxi1706@126.com
The optimization of robot manipulator’s trajectory has become a hot topic in academic and industrial fields. In this paper, a method for minimizing the moving distance of robot manipulators is presented. The Stanford Manipulator is used as the research object and the inverse kinematics model is established with Denavit-Hartenberg method. Base on the initial posture matrix, the inverse kinematics model is used to find the initial state of each joint. In accordance with the given beginning moment, cubic polynomial interpolation is applied to each joint variable and the positive kinematic model is used to calculate the moving distance of end effector. Genetic algorithm is used to optimize the sequential order of each joint and the time difference between different starting time of joints. Numerical applications involving a Stanford manipulator are presented.
© The authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.