CVROOct 2, 2019

OpenVSLAM: A Versatile Visual SLAM Framework

arXiv:1910.01122v3308 citationsHas Code
Originality Synthesis-oriented
AI Analysis

This work addresses the need for more accessible and extensible visual SLAM tools for researchers and developers in fields such as robotics and AR, though it appears incremental as it builds on existing frameworks.

The authors tackled the problem of conventional open-source visual SLAM frameworks not being designed as libraries for third-party programs by developing OpenVSLAM, a versatile framework with high usability and extensibility for applications like AR devices and autonomous robots.

In this paper, we introduce OpenVSLAM, a visual SLAM framework with high usability and extensibility. Visual SLAM systems are essential for AR devices, autonomous control of robots and drones, etc. However, conventional open-source visual SLAM frameworks are not appropriately designed as libraries called from third-party programs. To overcome this situation, we have developed a novel visual SLAM framework. This software is designed to be easily used and extended. It incorporates several useful features and functions for research and development.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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