Comparative analysis of ROS-based monocular SLAM methods for indoor navigation

Alexander Buyval; Ilya Afanasyev; Evgeni Magid

doi:10.1117/12.2268809

17 March 2017 Comparative analysis of ROS-based monocular SLAM methods for indoor navigation

Alexander Buyval, Ilya Afanasyev, Evgeni Magid

Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 103411K (2017) https://doi.org/10.1117/12.2268809
Event: Ninth International Conference on Machine Vision, 2016, Nice, France

Abstract

This paper presents a comparison of four most recent ROS-based monocular SLAM-related methods: ORB-SLAM, REMODE, LSD-SLAM, and DPPTAM, and analyzes their feasibility for a mobile robot application in indoor environment. We tested these methods using video data that was recorded from a conventional wide-angle full HD webcam with a rolling shutter. The camera was mounted on a human-operated prototype of an unmanned ground vehicle, which followed a closed-loop trajectory. Both feature-based methods (ORB-SLAM, REMODE) and direct SLAMrelated algorithms (LSD-SLAM, DPPTAM) demonstrated reasonably good results in detection of volumetric objects, corners, obstacles and other local features. However, we met difficulties with recovering typical for offices homogeneously colored walls, since all of these methods created empty spaces in a reconstructed sparse 3D scene. This may cause collisions of an autonomously guided robot with unfeatured walls and thus limits applicability of maps, which are obtained by the considered monocular SLAM-related methods for indoor robot navigation.

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Alexander Buyval, Ilya Afanasyev, and Evgeni Magid "Comparative analysis of ROS-based monocular SLAM methods for indoor navigation", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103411K (17 March 2017); https://doi.org/10.1117/12.2268809

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