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A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning

Cilt: 2 Sayı: 1 21 Haziran 2021
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A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning

Abstract

This study aims to create semantic and metric maps of a post-disaster indoor environment similar to standard the National Institute of Standards and Technology (NIST) search and rescue test arenas that first-responders can easily read. We prefer to use point cloud data acquired with an RGB-D camera since it does not be affected by post-disaster environments’ dusty and dull nature. Besides, each point cloud data is processed separately so that the semantic and metric maps grow incrementally. The Dynamic Graph Convolutional Neural Network (DGCNN) is used to classify points as sematic categories such as walls, terrain, and inclined and straight ramps. RTAB-Map and the semantic map are utilized to generate the octree-based 3D metric map. The experiments are conducted in a simulated environment modelled with Gazebo similar to NIST test arenas to show the effectiveness of the proposed method.

Keywords

Search and Rescue , Mobile Robot , 3D Semantic Map , 3D Metric Map , Point Cloud , Point-Based Deep Learning

Kaynakça

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Kaynak Göster

APA
Kocaoğlu, M., Işıkdemir, Y. E., Uzun, M. A., Turgut, K., Tas, M. O., & Kaleci, B. (2021). A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning. Journal of Science, Technology and Engineering Research, 2(1), 11-22. https://doi.org/10.5281/zenodo.4589489
AMA
1.Kocaoğlu M, Işıkdemir YE, Uzun MA, Turgut K, Tas MO, Kaleci B. A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning. Journal of Science, Technology and Engineering Research. 2021;2(1):11-22. doi:10.5281/zenodo.4589489
Chicago
Kocaoğlu, Muhammed, Yunus Emre Işıkdemir, Muhammed Ali Uzun, Kaya Turgut, Muhammed Oguz Tas, ve Burak Kaleci. 2021. “A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning”. Journal of Science, Technology and Engineering Research 2 (1): 11-22. https://doi.org/10.5281/zenodo.4589489.
EndNote
Kocaoğlu M, Işıkdemir YE, Uzun MA, Turgut K, Tas MO, Kaleci B (01 Haziran 2021) A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning. Journal of Science, Technology and Engineering Research 2 1 11–22.
IEEE
[1]M. Kocaoğlu, Y. E. Işıkdemir, M. A. Uzun, K. Turgut, M. O. Tas, ve B. Kaleci, “A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning”, Journal of Science, Technology and Engineering Research, c. 2, sy 1, ss. 11–22, Haz. 2021, doi: 10.5281/zenodo.4589489.
ISNAD
Kocaoğlu, Muhammed - Işıkdemir, Yunus Emre - Uzun, Muhammed Ali - Turgut, Kaya - Tas, Muhammed Oguz - Kaleci, Burak. “A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning”. Journal of Science, Technology and Engineering Research 2/1 (01 Haziran 2021): 11-22. https://doi.org/10.5281/zenodo.4589489.
JAMA
1.Kocaoğlu M, Işıkdemir YE, Uzun MA, Turgut K, Tas MO, Kaleci B. A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning. Journal of Science, Technology and Engineering Research. 2021;2:11–22.
MLA
Kocaoğlu, Muhammed, vd. “A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning”. Journal of Science, Technology and Engineering Research, c. 2, sy 1, Haziran 2021, ss. 11-22, doi:10.5281/zenodo.4589489.
Vancouver
1.Muhammed Kocaoğlu, Yunus Emre Işıkdemir, Muhammed Ali Uzun, Kaya Turgut, Muhammed Oguz Tas, Burak Kaleci. A Mobile Robot Application for Constructing Semantic and Metric Maps of Search and Rescue Arenas with Point-Based Deep Learning. Journal of Science, Technology and Engineering Research. 01 Haziran 2021;2(1):11-22. doi:10.5281/zenodo.4589489