Neural network-based robot localization using visual features
This paper outlines the development of a module capable of constructing a map-building algorithm using inertial odometry and visual features. It incorporates an object recognition module that leverages local features and unsupervised artificial neural networks to identify non-dynamic elements in a...
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| Format: | Article |
| Language: | English |
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Universidad Politécnica Salesiana
2024-10-01
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| Series: | Ingenius: Revista de Ciencia y Tecnología |
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| Online Access: | https://revistas.ups.edu.ec/index.php/ingenius/article/view/8052 |
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| author | Felipe Trujillo-Romero |
| author_facet | Felipe Trujillo-Romero |
| author_sort | Felipe Trujillo-Romero |
| collection | DOAJ |
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This paper outlines the development of a module capable of constructing a map-building algorithm using inertial odometry and visual features. It incorporates an object recognition module that leverages local features and unsupervised artificial neural networks to identify non-dynamic elements in a room and assign them positions. The map is modeled using a neural network, where each neuron corresponds to an absolute position in the room. Once the map is constructed, capturing just a couple of images of the environment is sufficient to estimate the robot's location. The experiments were conducted using both simulation and a real robot. The Webots environment with the virtual humanoid robot NAO was used for the simulations. Concurrently, results were obtained using a real NAO robot in a setting with various objects. The results demonstrate notable precision in localization within the two-dimensional maps, achieving an accuracy of ± (0.06, 0.1) m in simulations contrasted with the natural environment, where the best value achieved was ± (0.25, 0.16) m.
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| format | Article |
| id | doaj-art-acef715a5a7541e1b21542c24666fd6f |
| institution | Kabale University |
| issn | 1390-650X 1390-860X |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Universidad Politécnica Salesiana |
| record_format | Article |
| series | Ingenius: Revista de Ciencia y Tecnología |
| spelling | doaj-art-acef715a5a7541e1b21542c24666fd6f2025-02-07T16:30:14ZengUniversidad Politécnica SalesianaIngenius: Revista de Ciencia y Tecnología1390-650X1390-860X2024-10-013210.17163/ings.n32.2024.08Neural network-based robot localization using visual featuresFelipe Trujillo-Romero0https://orcid.org/0000-0003-3755-2637Universidad de Guanajuato This paper outlines the development of a module capable of constructing a map-building algorithm using inertial odometry and visual features. It incorporates an object recognition module that leverages local features and unsupervised artificial neural networks to identify non-dynamic elements in a room and assign them positions. The map is modeled using a neural network, where each neuron corresponds to an absolute position in the room. Once the map is constructed, capturing just a couple of images of the environment is sufficient to estimate the robot's location. The experiments were conducted using both simulation and a real robot. The Webots environment with the virtual humanoid robot NAO was used for the simulations. Concurrently, results were obtained using a real NAO robot in a setting with various objects. The results demonstrate notable precision in localization within the two-dimensional maps, achieving an accuracy of ± (0.06, 0.1) m in simulations contrasted with the natural environment, where the best value achieved was ± (0.25, 0.16) m. https://revistas.ups.edu.ec/index.php/ingenius/article/view/8052Visual FeaturesBidimensional MapsInertial OdometryHumanoid Robot NAOA-KAZE descriptorGrowing Cell Structure |
| spellingShingle | Felipe Trujillo-Romero Neural network-based robot localization using visual features Ingenius: Revista de Ciencia y Tecnología Visual Features Bidimensional Maps Inertial Odometry Humanoid Robot NAO A-KAZE descriptor Growing Cell Structure |
| title | Neural network-based robot localization using visual features |
| title_full | Neural network-based robot localization using visual features |
| title_fullStr | Neural network-based robot localization using visual features |
| title_full_unstemmed | Neural network-based robot localization using visual features |
| title_short | Neural network-based robot localization using visual features |
| title_sort | neural network based robot localization using visual features |
| topic | Visual Features Bidimensional Maps Inertial Odometry Humanoid Robot NAO A-KAZE descriptor Growing Cell Structure |
| url | https://revistas.ups.edu.ec/index.php/ingenius/article/view/8052 |
| work_keys_str_mv | AT felipetrujilloromero neuralnetworkbasedrobotlocalizationusingvisualfeatures |