Topomap: Topological Mapping and Navigation Based on Visual SLAM Maps
Fabian Bl\"ochliger, Marius Fehr, Marcin Dymczyk, Thomas Schneider and, Roland Siegwart

TL;DR
Topomap introduces a novel topological mapping framework that converts sparse visual SLAM maps into 3D topological maps, enhancing global planning efficiency and reducing computational costs in robot navigation.
Contribution
It presents a new method to transform sparse SLAM maps into topological maps for improved path planning in large-scale environments.
Findings
Achieves similar planning performance as RRT*
Reduces computation time and storage requirements
Demonstrates effectiveness on real-world robotic platform
Abstract
Visual robot navigation within large-scale, semi-structured environments deals with various challenges such as computation intensive path planning algorithms or insufficient knowledge about traversable spaces. Moreover, many state-of-the-art navigation approaches only operate locally instead of gaining a more conceptual understanding of the planning objective. This limits the complexity of tasks a robot can accomplish and makes it harder to deal with uncertainties that are present in the context of real-time robotics applications. In this work, we present Topomap, a framework which simplifies the navigation task by providing a map to the robot which is tailored for path planning use. This novel approach transforms a sparse feature-based map from a visual Simultaneous Localization And Mapping (SLAM) system into a three-dimensional topological map. This is done in two steps. First, we…
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