Computationally Efficient Cooperative Dynamic Range-Only SLAM Based on Sum of Gaussian Filter
A cooperative dynamic range-only simultaneous localization and mapping (CDRO-SLAM) algorithm based on the sum of Gaussian (SoG) filter was recently introduced. The main characteristics of the CDRO-SLAM are (i) the integration of inter-node ranges as well as usual direct robot-node ranges to improve...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/11/3306 |
| _version_ | 1797565663714213888 |
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| author | Jung-Hee Kim Doik Kim |
| author_facet | Jung-Hee Kim Doik Kim |
| author_sort | Jung-Hee Kim |
| collection | DOAJ |
| description | A cooperative dynamic range-only simultaneous localization and mapping (CDRO-SLAM) algorithm based on the sum of Gaussian (SoG) filter was recently introduced. The main characteristics of the CDRO-SLAM are (i) the integration of inter-node ranges as well as usual direct robot-node ranges to improve the convergence rate and localization accuracy and (ii) the tracking of any moving nodes under dynamic environments by resetting and updating the SoG variables. In this paper, an efficient implementation of the CDRO-SLAM (eCDRO-SLAM) is proposed to mitigate the high computational burden of the CDRO-SLAM due to the inter-node measurements. Furthermore, a thorough computational analysis is presented, which reveals that the computational efficiency of the eCDRO-SLAM is significantly improved over the CDRO-SLAM. The performance of the proposed eCDRO-SLAM is compared with those of several conventional RO-SLAM algorithms and the results show that the proposed efficient algorithm has a faster convergence rate and a similar map estimation error regardless of the map size. Accordingly, the proposed eCDRO-SLAM can be utilized in various RO-SLAM applications. |
| first_indexed | 2024-03-10T19:15:14Z |
| format | Article |
| id | doaj.art-9c1eb3ad1ebd4d11bd9c177a6597d2ac |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T19:15:14Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9c1eb3ad1ebd4d11bd9c177a6597d2ac2023-11-20T03:26:06ZengMDPI AGSensors1424-82202020-06-012011330610.3390/s20113306Computationally Efficient Cooperative Dynamic Range-Only SLAM Based on Sum of Gaussian FilterJung-Hee Kim0Doik Kim1Department of Electronic Engineering, Hanyang University, Seoul 04763, KoreaCenter for Intelligent and Interactive Robotics, Korea Institute of Science and Technology, Seoul 02792, KoreaA cooperative dynamic range-only simultaneous localization and mapping (CDRO-SLAM) algorithm based on the sum of Gaussian (SoG) filter was recently introduced. The main characteristics of the CDRO-SLAM are (i) the integration of inter-node ranges as well as usual direct robot-node ranges to improve the convergence rate and localization accuracy and (ii) the tracking of any moving nodes under dynamic environments by resetting and updating the SoG variables. In this paper, an efficient implementation of the CDRO-SLAM (eCDRO-SLAM) is proposed to mitigate the high computational burden of the CDRO-SLAM due to the inter-node measurements. Furthermore, a thorough computational analysis is presented, which reveals that the computational efficiency of the eCDRO-SLAM is significantly improved over the CDRO-SLAM. The performance of the proposed eCDRO-SLAM is compared with those of several conventional RO-SLAM algorithms and the results show that the proposed efficient algorithm has a faster convergence rate and a similar map estimation error regardless of the map size. Accordingly, the proposed eCDRO-SLAM can be utilized in various RO-SLAM applications.https://www.mdpi.com/1424-8220/20/11/3306simultaneous localization and mapping (SLAM)range-only SLAMsum of Gaussian (SoG) filtercooperative approach |
| spellingShingle | Jung-Hee Kim Doik Kim Computationally Efficient Cooperative Dynamic Range-Only SLAM Based on Sum of Gaussian Filter Sensors simultaneous localization and mapping (SLAM) range-only SLAM sum of Gaussian (SoG) filter cooperative approach |
| title | Computationally Efficient Cooperative Dynamic Range-Only SLAM Based on Sum of Gaussian Filter |
| title_full | Computationally Efficient Cooperative Dynamic Range-Only SLAM Based on Sum of Gaussian Filter |
| title_fullStr | Computationally Efficient Cooperative Dynamic Range-Only SLAM Based on Sum of Gaussian Filter |
| title_full_unstemmed | Computationally Efficient Cooperative Dynamic Range-Only SLAM Based on Sum of Gaussian Filter |
| title_short | Computationally Efficient Cooperative Dynamic Range-Only SLAM Based on Sum of Gaussian Filter |
| title_sort | computationally efficient cooperative dynamic range only slam based on sum of gaussian filter |
| topic | simultaneous localization and mapping (SLAM) range-only SLAM sum of Gaussian (SoG) filter cooperative approach |
| url | https://www.mdpi.com/1424-8220/20/11/3306 |
| work_keys_str_mv | AT jungheekim computationallyefficientcooperativedynamicrangeonlyslambasedonsumofgaussianfilter AT doikkim computationallyefficientcooperativedynamicrangeonlyslambasedonsumofgaussianfilter |