Development of a New Technique in ROS for Mobile Robots Localization in Known-Based 2D Environments
Keywords:
Particle filters, Robot operating system, Pose estimation, Monte Carlo Localization, amcl, Localization in ROS.Abstract
Adaptive Monte Carlo Localization (amcl) is the only standard package for mobile robots localization in Robot Operating System (ROS). In this research, a new particle filter based localization technique named general Monte Carlo Localization (gmcl) was developed by adding three particle filter algorithms to amcl in order to improve its performance, so the new versions of ROS could be better invested in systems that depend on the knowledge of the robot’s pose.
In addition, we compared amcl and gmcl in terms of computational complexity and the ability of addressing the pose-estimation problem in a differential drive mobile robot equipped with a LiDAR sensor. The results showed that the new proposed technique outperformed amcl in the accuracy of estimating the pose when compared to the same maximal computational workload. gmcl was able to reduce the pose-error in pose tracking and also able to increase the success rate of robot’s pose detection in the two problems of global localization and kidnapped-robot.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 https://creativecommons.org/licenses/by-nc-sa/4.0/
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The authors retain the copyright and grant the right to publish in the magazine for the first time with the transfer of the commercial right to Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series
Under a CC BY- NC-SA 04 license that allows others to share the work with of the work's authorship and initial publication in this journal. Authors can use a copy of their articles in their scientific activity, and on their scientific websites, provided that the place of publication is indicted in Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series . The Readers have the right to send, print and subscribe to the initial version of the article, and the title of Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series Publisher
journal uses a CC BY-NC-SA license which mean
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material
- The licensor cannot revoke these freedoms as long as you follow the license terms.
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
- ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
