Open AccessOnboard dynamic RGB‐D simultaneous localization and mapping for mobile robot navigation
Author(s) -
Canovas Bruce,
Nègre Amaury,
Rombaut Michèle
Publication year - 2021
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.2021-0061
Subject(s) - robustness (evolution) , simultaneous localization and mapping , mobile robot , computer vision , computer science , artificial intelligence , robot , motion planning , rgb color model , mobile robot navigation , global positioning system , robot control , telecommunications , biochemistry , chemistry , gene
Although the actual visual simultaneous localization and mapping (SLAM) algorithms provide highly accurate tracking and mapping, most algorithms are too heavy to run live on embedded devices. In addition, the maps they produce are often unsuitable for path planning. To mitigate these issues, we propose a completely closed‐loop online dense RGB‐D SLAM algorithm targeting autonomous indoor mobile robot navigation tasks. The proposed algorithm runs live on an NVIDIA Jetson board embedded on a two‐wheel differential‐drive robot. It exhibits lightweight three‐dimensional mapping, room‐scale consistency, accurate pose tracking, and robustness to moving objects. Further, we introduce a navigation strategy based on the proposed algorithm. Experimental results demonstrate the robustness of the proposed SLAM algorithm, its computational efficiency, and its benefits for on‐the‐fly navigation while mapping.