Unsupervised place recognition for assistive mobile robots based on local feature descriptions.
Place recognition is an important perceptual robotic problem, especially in the navigation process. Previous place-recognition approaches have been used for solving ‘global localization’ and ‘kidnapped robot’ problems. Such approaches are usually performed in a supervised mode. In this paper, a robu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
| Published: |
SAGE Publications
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/23443/ http://psasir.upm.edu.my/id/eprint/23443/1/Unsupervised%20place%20recognition%20for%20assistive%20mobile%20robots%20based%20on%20local%20feature%20descriptions.pdf |
| _version_ | 1848844759081156608 |
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| author | Tang, Sai Hong Ramli, Abdul Rahman Samsudin, Khairulmizam |
| author_facet | Tang, Sai Hong Ramli, Abdul Rahman Samsudin, Khairulmizam |
| author_sort | Tang, Sai Hong |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Place recognition is an important perceptual robotic problem, especially in the navigation process. Previous place-recognition approaches have been used for solving ‘global localization’ and ‘kidnapped robot’ problems. Such approaches are usually performed in a supervised mode. In this paper, a robust appearance-based unsupervised place clustering and recognition algorithm is introduced. This method fuses several image features using speed up robust features (SURF) by agglomerating them into a union form of features inside each place cluster. The number of place clusters can be extracted by investigating the SURF-based scene similarity diagram between adjacent images. During a human-guided learning step, the robot captures visual information acquired by an embedded camera and converts them into topological place clusters. Experimental results show the robustness, accuracy, and efficiency of the method, as well as its ability to create topological place clusters for solving global localization and kidnapped robot problems. The performance of the developed system is remarkable in terms of time, clustering error, and recognition precision. |
| first_indexed | 2025-11-15T08:36:01Z |
| format | Article |
| id | upm-23443 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T08:36:01Z |
| publishDate | 2011 |
| publisher | SAGE Publications |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-234432016-01-12T07:06:48Z http://psasir.upm.edu.my/id/eprint/23443/ Unsupervised place recognition for assistive mobile robots based on local feature descriptions. Tang, Sai Hong Ramli, Abdul Rahman Samsudin, Khairulmizam Place recognition is an important perceptual robotic problem, especially in the navigation process. Previous place-recognition approaches have been used for solving ‘global localization’ and ‘kidnapped robot’ problems. Such approaches are usually performed in a supervised mode. In this paper, a robust appearance-based unsupervised place clustering and recognition algorithm is introduced. This method fuses several image features using speed up robust features (SURF) by agglomerating them into a union form of features inside each place cluster. The number of place clusters can be extracted by investigating the SURF-based scene similarity diagram between adjacent images. During a human-guided learning step, the robot captures visual information acquired by an embedded camera and converts them into topological place clusters. Experimental results show the robustness, accuracy, and efficiency of the method, as well as its ability to create topological place clusters for solving global localization and kidnapped robot problems. The performance of the developed system is remarkable in terms of time, clustering error, and recognition precision. SAGE Publications 2011 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/23443/1/Unsupervised%20place%20recognition%20for%20assistive%20mobile%20robots%20based%20on%20local%20feature%20descriptions.pdf Tang, Sai Hong and Ramli, Abdul Rahman and Samsudin, Khairulmizam (2011) Unsupervised place recognition for assistive mobile robots based on local feature descriptions. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 225 (8). pp. 1068-1085. ISSN 0959-6518 10.1177/0959651811406641 English |
| spellingShingle | Tang, Sai Hong Ramli, Abdul Rahman Samsudin, Khairulmizam Unsupervised place recognition for assistive mobile robots based on local feature descriptions. |
| title | Unsupervised place recognition for assistive mobile robots based on local feature descriptions. |
| title_full | Unsupervised place recognition for assistive mobile robots based on local feature descriptions. |
| title_fullStr | Unsupervised place recognition for assistive mobile robots based on local feature descriptions. |
| title_full_unstemmed | Unsupervised place recognition for assistive mobile robots based on local feature descriptions. |
| title_short | Unsupervised place recognition for assistive mobile robots based on local feature descriptions. |
| title_sort | unsupervised place recognition for assistive mobile robots based on local feature descriptions. |
| url | http://psasir.upm.edu.my/id/eprint/23443/ http://psasir.upm.edu.my/id/eprint/23443/ http://psasir.upm.edu.my/id/eprint/23443/1/Unsupervised%20place%20recognition%20for%20assistive%20mobile%20robots%20based%20on%20local%20feature%20descriptions.pdf |