| アイテムタイプ |
共通アイテムタイプ(1) |
| 公開日 |
2025-03-05 |
| タイトル |
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|
タイトル |
A Study on Parameter Optimization Based on Fireworks Algorithm for SLAM Algorithm |
|
言語 |
en |
| 著者 |
Fujino, Tomoaki
田向, 権
Uchibori, Akihiko
Kubota, Ryosuke
|
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
In recent years, Simultaneous Localization and Mapping (SLAM) has been the subject of various studies with potential applications in a wide range of fields such as automated driving and service robots[1]. Cartographer[2] developed by Google is a type of graph-based SLAM. It is highly accurate, however, it has many parameters to be adjusted. It is necessary to consider the uncertainty of sensor data obtained from the real environment to use SLAM effectively. The objective of this study is to automatically adjust the translation and rotation confidence weights of the local SLAM and the odometry translation and rotation confidence weights that recognize the environment around the robot to optimize the robot's movement trajectory, which affects the accuracy of the generated environment map. We propose an automatic parameter adjustment method using the Fireworks Algorithm (FA)[3], one of the swarm intelligence algorithms for optimization, and dead reckoning[4], a self-positioning method using internal sensors. In simulator environments, we set the parameter that we searched for by default parameter of TurtleBot3[5] and it searched for by FA and proposed method to running Cartographer. After that, based on the generated environmental map, the mobile robot is moved to the destination, and the error in the amount of movement is quantitatively evaluated as fitness. |
|
言語 |
en |
| 備考 |
|
|
内容記述タイプ |
Other |
|
内容記述 |
11th International Symposium on Applied Engineering and Sciences (SAES2023), November 20 - 21, 2023, Universiti Putra Malaysia, Malaysia |
|
言語 |
en |
| 書誌情報 |
発行日 2023-11
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| キーワード |
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|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
SLAM |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Gazebo |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Fireworks Algorithm |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Mobile Robotics |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
TurtleBot |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_5794 |
|
資源タイプ |
conference paper |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| 会議記述 |
|
|
|
会議名 |
11th International Symposium on Applied Engineering and Sciences (SAES2023) |
|
|
言語 |
en |
|
回次 |
11 |
|
|
開始年 |
2023 |
|
|
開始月 |
11 |
|
|
開始日 |
20 |
|
|
終了年 |
2024 |
|
|
終了月 |
11 |
|
|
終了日 |
21 |
|
開催国 |
MYS |
| 研究者情報 |
|
|
URL |
https://hyokadb02.jimu.kyutech.ac.jp/html/100000641_ja.html |
| 論文ID（連携） |
|
|
値 |
10435147 |
| 連携ID |
|
|
値 |
13578 |
10435147.pdf (212.4 KB)
