Room Detection for Topological Maps
S\"oren Schwertfeger, Tianyan Yu

TL;DR
This paper enhances topological map evaluation for robotics by integrating room detection using alpha shapes into the topology graph, improving robustness and stability in map comparison.
Contribution
It introduces a method to detect open areas like rooms in 2D grid maps and incorporates them into topological representations, extending previous work.
Findings
Improved stability in topology graph matching.
Enhanced robustness in map evaluation.
Effective room detection using alpha shapes.
Abstract
Mapping is an important part of many robotic applications. In order to measure the performance of the mapping process we have to measure the quality of its result: the map. The map is essential for robotic algorithms like localization and path planning. Previously it was shown how matched Topology Graphs can be used for map evaluation by comparing the topology of the robot generated map to the topology of a ground truth map. In this paper we are extending the previous work by detecting open areas, for example rooms, in the 2D grid map and adding those to the topological representation. This way we can avoid the unreliable generation of paths in open areas, thus making the Topology Graph generation, and through that also the Topology Graph matching, more stable and robust. The detection applies the alpha shape algorithm for room detection.
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Taxonomy
TopicsRobotics and Sensor-Based Localization · Robotic Path Planning Algorithms · Advanced Image and Video Retrieval Techniques
