A Visual Navigation Method of Mobile Robot Using a Sketched Semantic Map
A new visual navigation method for a mobile robot is proposed in this paper. Its originality lies in integrating a sketched map with a semantic map together for the robot's navigation and in using unified tags to help recognize landmarks. In this sketched semantic map, the outline and semantic...
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2012-10-01
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Series: | International Journal of Advanced Robotic Systems |
Online Access: | https://doi.org/10.5772/52501 |
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doaj-d7f84d78290c4cc4b744a4bd27e7496b2020-11-25T01:27:14ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142012-10-01910.5772/5250110.5772_52501A Visual Navigation Method of Mobile Robot Using a Sketched Semantic MapXinde Li0Xiulong Zhang1Bo Zhu2Xianzhong Dai3 Key Laboratory of Measurement and Control of CSE (Ministry of Education), School of Automation, Southeast University, Nanjing, China Key Laboratory of Measurement and Control of CSE (Ministry of Education), School of Automation, Southeast University, Nanjing, China Key Laboratory of Measurement and Control of CSE (Ministry of Education), School of Automation, Southeast University, Nanjing, China Key Laboratory of Measurement and Control of CSE (Ministry of Education), School of Automation, Southeast University, Nanjing, ChinaA new visual navigation method for a mobile robot is proposed in this paper. Its originality lies in integrating a sketched map with a semantic map together for the robot's navigation and in using unified tags to help recognize landmarks. In this sketched semantic map, the outline and semantic information of key referenced objects are used to represent themselves and a rough route for the robot's navigation is also sketched. Over the course of robot navigation along the route, and in order to easily recognize the referenced objects from the complex background, a kind of unified label is designed and pasted on the potential referenced objects in advance. A recognition method based on the Pseudo-Zernike Moment and the Normalized Moment of Inertia is used to compute the matching degree between the real-time image of the referenced object and its similar outline in a database. In addition, the odometer information is also fused so as to roughly localize the robot. Finally, through a series of experiments, the advantage and efficiency of the new navigation method with real-time dynamic obstacle avoidance are testified with the help of the imprecise real map and route.https://doi.org/10.5772/52501 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xinde Li Xiulong Zhang Bo Zhu Xianzhong Dai |
spellingShingle |
Xinde Li Xiulong Zhang Bo Zhu Xianzhong Dai A Visual Navigation Method of Mobile Robot Using a Sketched Semantic Map International Journal of Advanced Robotic Systems |
author_facet |
Xinde Li Xiulong Zhang Bo Zhu Xianzhong Dai |
author_sort |
Xinde Li |
title |
A Visual Navigation Method of Mobile Robot Using a Sketched Semantic Map |
title_short |
A Visual Navigation Method of Mobile Robot Using a Sketched Semantic Map |
title_full |
A Visual Navigation Method of Mobile Robot Using a Sketched Semantic Map |
title_fullStr |
A Visual Navigation Method of Mobile Robot Using a Sketched Semantic Map |
title_full_unstemmed |
A Visual Navigation Method of Mobile Robot Using a Sketched Semantic Map |
title_sort |
visual navigation method of mobile robot using a sketched semantic map |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2012-10-01 |
description |
A new visual navigation method for a mobile robot is proposed in this paper. Its originality lies in integrating a sketched map with a semantic map together for the robot's navigation and in using unified tags to help recognize landmarks. In this sketched semantic map, the outline and semantic information of key referenced objects are used to represent themselves and a rough route for the robot's navigation is also sketched. Over the course of robot navigation along the route, and in order to easily recognize the referenced objects from the complex background, a kind of unified label is designed and pasted on the potential referenced objects in advance. A recognition method based on the Pseudo-Zernike Moment and the Normalized Moment of Inertia is used to compute the matching degree between the real-time image of the referenced object and its similar outline in a database. In addition, the odometer information is also fused so as to roughly localize the robot. Finally, through a series of experiments, the advantage and efficiency of the new navigation method with real-time dynamic obstacle avoidance are testified with the help of the imprecise real map and route. |
url |
https://doi.org/10.5772/52501 |
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