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The main novelty of the present work is a method for 3D OOI reconstruction based on a 2D map, thereby retaining the fast performances of the latter. A theory is established that is adapted to a SAR environment, including the object identification, exploration area coverage (AC), and loop closure detection of revisited spots. Proposed for the first is image optical flow calculation with a 2D\/3D fusion method and RGB-D (red, green, blue + depth) transformation based on Joblove\u2013Greenberg mathematics and OpenCV processing. The mathematical theories of optical flow calculation and wavelet transformation are used for the first time to solve the robotic SAR SLAM problem. The present contributions indicate two aspects: (i) mobile robots depend on planar distance estimation to build 2D maps quickly and to provide SAR exploration AC; (ii) 3D OOIs are reconstructed using the proposed innovative methods of RGB-D iterative closest points (RGB-ICPs) and 2D\/3D principle of wavelet transformation. Different mobile robots are used to conduct indoor and outdoor SAR SLAM. Both the SLAM and the SAR OOIs detection are implemented by simulations and ground-truth experiments, which provide strong evidence for the proposed 2D\/3D reconstruction SAR SLAM approaches adapted to post-disaster environments.<\/jats:p>","DOI":"10.1017\/s0263574719000675","type":"journal-article","created":{"date-parts":[[2019,5,21]],"date-time":"2019-05-21T08:06:39Z","timestamp":1558425999000},"page":"350-373","source":"Crossref","is-referenced-by-count":41,"title":["Three-Dimensional Reconstruction Based on Visual SLAM of Mobile Robot in Search and Rescue Disaster Scenarios"],"prefix":"10.1017","volume":"38","author":[{"given":"Hongling","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengjin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bao","family":"Pang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangyuan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2019,5,21]]},"reference":[{"key":"S0263574719000675_ref49","unstructured":"49. 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