Cargando…
Precision-Driven Multi-Target Path Planning and Fine Position Error Estimation on a Dual-Movement-Mode Mobile Robot Using a Three-Parameter Error Model
The multi-target path planning problem is a universal problem to mobile robots and mobile manipulators. The two movement modes of forward movement and rotation are universally implemented in integrated, commercially accessible mobile platforms used in logistics robots, construction robots, etc. Loca...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823822/ https://www.ncbi.nlm.nih.gov/pubmed/36617117 http://dx.doi.org/10.3390/s23010517 |
_version_ | 1784866256722067456 |
---|---|
author | Ji, Junjie Zhao, Jing-Shan Misyurin, Sergey Yurievich Martins, Daniel |
author_facet | Ji, Junjie Zhao, Jing-Shan Misyurin, Sergey Yurievich Martins, Daniel |
author_sort | Ji, Junjie |
collection | PubMed |
description | The multi-target path planning problem is a universal problem to mobile robots and mobile manipulators. The two movement modes of forward movement and rotation are universally implemented in integrated, commercially accessible mobile platforms used in logistics robots, construction robots, etc. Localization error in multi-target path tracking is one of the crucial measures in mobile robot applications. In this article, a precision-driven multi-target path planning is first proposed. According to the path’s odometry error evaluation function, the precision-optimized path can be discovered. Then, a three-parameter odometry error model is proposed based on the dual movement mode. The error model describes localization errors in terms of the theoretical motion command values issued to the mobile robot, the forward moving distances, and the rotation angles. It appears that the three error parameters follow the normal distribution. The error model is finally validated using a mobile robot prototype. The error parameters can be identified by analyzing the actual moving trajectory of arbitrary movements. The experimental localization error is compared to the simulated localization error in order to validate the proposed error model and the precision-driven path planning method. The OptiTrack motion capture device was used to capture the prototype mobile robot’s pose and position data. |
format | Online Article Text |
id | pubmed-9823822 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98238222023-01-08 Precision-Driven Multi-Target Path Planning and Fine Position Error Estimation on a Dual-Movement-Mode Mobile Robot Using a Three-Parameter Error Model Ji, Junjie Zhao, Jing-Shan Misyurin, Sergey Yurievich Martins, Daniel Sensors (Basel) Article The multi-target path planning problem is a universal problem to mobile robots and mobile manipulators. The two movement modes of forward movement and rotation are universally implemented in integrated, commercially accessible mobile platforms used in logistics robots, construction robots, etc. Localization error in multi-target path tracking is one of the crucial measures in mobile robot applications. In this article, a precision-driven multi-target path planning is first proposed. According to the path’s odometry error evaluation function, the precision-optimized path can be discovered. Then, a three-parameter odometry error model is proposed based on the dual movement mode. The error model describes localization errors in terms of the theoretical motion command values issued to the mobile robot, the forward moving distances, and the rotation angles. It appears that the three error parameters follow the normal distribution. The error model is finally validated using a mobile robot prototype. The error parameters can be identified by analyzing the actual moving trajectory of arbitrary movements. The experimental localization error is compared to the simulated localization error in order to validate the proposed error model and the precision-driven path planning method. The OptiTrack motion capture device was used to capture the prototype mobile robot’s pose and position data. MDPI 2023-01-03 /pmc/articles/PMC9823822/ /pubmed/36617117 http://dx.doi.org/10.3390/s23010517 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ji, Junjie Zhao, Jing-Shan Misyurin, Sergey Yurievich Martins, Daniel Precision-Driven Multi-Target Path Planning and Fine Position Error Estimation on a Dual-Movement-Mode Mobile Robot Using a Three-Parameter Error Model |
title | Precision-Driven Multi-Target Path Planning and Fine Position Error Estimation on a Dual-Movement-Mode Mobile Robot Using a Three-Parameter Error Model |
title_full | Precision-Driven Multi-Target Path Planning and Fine Position Error Estimation on a Dual-Movement-Mode Mobile Robot Using a Three-Parameter Error Model |
title_fullStr | Precision-Driven Multi-Target Path Planning and Fine Position Error Estimation on a Dual-Movement-Mode Mobile Robot Using a Three-Parameter Error Model |
title_full_unstemmed | Precision-Driven Multi-Target Path Planning and Fine Position Error Estimation on a Dual-Movement-Mode Mobile Robot Using a Three-Parameter Error Model |
title_short | Precision-Driven Multi-Target Path Planning and Fine Position Error Estimation on a Dual-Movement-Mode Mobile Robot Using a Three-Parameter Error Model |
title_sort | precision-driven multi-target path planning and fine position error estimation on a dual-movement-mode mobile robot using a three-parameter error model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823822/ https://www.ncbi.nlm.nih.gov/pubmed/36617117 http://dx.doi.org/10.3390/s23010517 |
work_keys_str_mv | AT jijunjie precisiondrivenmultitargetpathplanningandfinepositionerrorestimationonadualmovementmodemobilerobotusingathreeparametererrormodel AT zhaojingshan precisiondrivenmultitargetpathplanningandfinepositionerrorestimationonadualmovementmodemobilerobotusingathreeparametererrormodel AT misyurinsergeyyurievich precisiondrivenmultitargetpathplanningandfinepositionerrorestimationonadualmovementmodemobilerobotusingathreeparametererrormodel AT martinsdaniel precisiondrivenmultitargetpathplanningandfinepositionerrorestimationonadualmovementmodemobilerobotusingathreeparametererrormodel |