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. 2021 Sep 23;21(19):6355.
doi: 10.3390/s21196355.

Semantics Aware Dynamic SLAM Based on 3D MODT

Muhammad Sualeh  1 , Gon-Woo Kim  1
Affiliations

Semantics Aware Dynamic SLAM Based on 3D MODT

Muhammad Sualeh et al. Sensors (Basel). .

Abstract

The idea of SLAM (Simultaneous Localization and Mapping) being a solved problem revolves around the static world assumption, even though autonomous systems are gaining environmental perception capabilities by exploiting the advances in computer vision and data-driven approaches. The computational demands and time complexities remain the main impediment in the effective fusion of the paradigms. In this paper, a framework to solve the dynamic SLAM problem is proposed. The dynamic regions of the scene are handled by making use of Visual-LiDAR based MODT (Multiple Object Detection and Tracking). Furthermore, minimal computational demands and real-time performance are ensured. The framework is tested on the KITTI Datasets and evaluated against the publicly available evaluation tools for a fair comparison with state-of-the-art SLAM algorithms. The results suggest that the proposed dynamic SLAM framework can perform in real-time with budgeted computational resources. In addition, the fused MODT provides rich semantic information that can be readily integrated into SLAM.

Keywords: 3D multiple object detection; dynamic SLAM; multiple object tracking; semantics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Framework for joint MODT and SLAM.
Figure 2
Figure 2
Proposed MODT integrated Dynamic SLAM framework.
Figure 3
Figure 3
3D MODT module in the proposed framework.
Figure 4
Figure 4
Camera-LiDAR Fusion Module.
Figure 5
Figure 5
Visual-LiDAR based Mask generated in comparison with Mask R CNN.
Figure 6
Figure 6
Dynamic SLAM with Visual-LiDAR based dynamic object mask.
Figure 7
Figure 7
Estimated trajectories of sequence 20 from KITTI Tracking Dataset.
See this image and copyright information in PMC

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