Occupancy grid map algorithm with neural network using array of infrared sensors
Occupancy grid map is a map representation that shows the occupancy of spaces, whether there is any object in a particular area or it is a free space. This map representation is also commonly known as a grid map. However, the accuracy of the occupancy grid map is highly dependent on the accuracy of...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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IOP Publishing
2020
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| Subjects: | |
| Online Access: | https://umpir.ump.edu.my/id/eprint/29374/ |
| _version_ | 1848827279197601792 |
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| author | N A, Yatim N, Buniyamin Z M, Noh Nur Aqilah, Othman |
| author_facet | N A, Yatim N, Buniyamin Z M, Noh Nur Aqilah, Othman |
| author_sort | N A, Yatim |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Occupancy grid map is a map representation that shows the occupancy of spaces, whether there is any object in a particular area or it is a free space. This map representation is also commonly known as a grid map. However, the accuracy of the occupancy grid map is highly dependent on the accuracy of the sensors. In this paper, low cost and noisy sensors such as infrared sensors were used with the occupancy grid map algorithm integrated with a neural network. The neural network was used to interpret adjacent sensor measurements into cell’s occupancy value in the grid map. From the simulation experiments, it is observed that, that neural network-integrated algorithm has a better map estimate throughout robot’s navigation with mean of 28% more accurate compared to occupancy grid map algorithm without neural network. This finding is beneficial for implementation with simultaneous localization and mapping or commonly known as SLAM problem. This is because SLAM algorithm makes use of both estimations of environment’s map and robot’s state. Thus, a better map estimate throughout the robot’s journey can improve a robot’s state estimate as well. |
| first_indexed | 2025-11-15T03:58:11Z |
| format | Conference or Workshop Item |
| id | ump-29374 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:58:11Z |
| publishDate | 2020 |
| publisher | IOP Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-293742025-10-02T07:49:03Z https://umpir.ump.edu.my/id/eprint/29374/ Occupancy grid map algorithm with neural network using array of infrared sensors N A, Yatim N, Buniyamin Z M, Noh Nur Aqilah, Othman TK Electrical engineering. Electronics Nuclear engineering Occupancy grid map is a map representation that shows the occupancy of spaces, whether there is any object in a particular area or it is a free space. This map representation is also commonly known as a grid map. However, the accuracy of the occupancy grid map is highly dependent on the accuracy of the sensors. In this paper, low cost and noisy sensors such as infrared sensors were used with the occupancy grid map algorithm integrated with a neural network. The neural network was used to interpret adjacent sensor measurements into cell’s occupancy value in the grid map. From the simulation experiments, it is observed that, that neural network-integrated algorithm has a better map estimate throughout robot’s navigation with mean of 28% more accurate compared to occupancy grid map algorithm without neural network. This finding is beneficial for implementation with simultaneous localization and mapping or commonly known as SLAM problem. This is because SLAM algorithm makes use of both estimations of environment’s map and robot’s state. Thus, a better map estimate throughout the robot’s journey can improve a robot’s state estimate as well. IOP Publishing 2020 Conference or Workshop Item PeerReviewed pdf en cc_by https://umpir.ump.edu.my/id/eprint/29374/1/35.%20Occupancy%20grid%20map%20algorithm%20with%20neural%20network%20using%20array%20of%20infrared%20sensors.pdf N A, Yatim and N, Buniyamin and Z M, Noh and Nur Aqilah, Othman (2020) Occupancy grid map algorithm with neural network using array of infrared sensors. In: Journal of Physics: Conference Series. International Conference on Telecommunication, Electronic and Computer Engineering 2019, ICTEC 2019 , 22-24 October 2019 , Melaka, Malaysia. pp. 1-10., 1502 (012053). ISSN 1742-6588 (print); 1742-6596 (online) (Published) https://doi.org/10.1088/1742-6596/1502/1/012053 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering N A, Yatim N, Buniyamin Z M, Noh Nur Aqilah, Othman Occupancy grid map algorithm with neural network using array of infrared sensors |
| title | Occupancy grid map algorithm with neural network using array of infrared sensors |
| title_full | Occupancy grid map algorithm with neural network using array of infrared sensors |
| title_fullStr | Occupancy grid map algorithm with neural network using array of infrared sensors |
| title_full_unstemmed | Occupancy grid map algorithm with neural network using array of infrared sensors |
| title_short | Occupancy grid map algorithm with neural network using array of infrared sensors |
| title_sort | occupancy grid map algorithm with neural network using array of infrared sensors |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | https://umpir.ump.edu.my/id/eprint/29374/ https://umpir.ump.edu.my/id/eprint/29374/ |