In this work, we fully define the existing relationships between traditional optimality criteria and the connectivity of the underlying pose-graph in Active SLAM, characterizing, therefore, the connection between Graph Theory and the Theory Optimal Experimental Design. We validate the proposed relationships in 2D and 3D graph SLAM datasets, showing a remarkable relaxation of the computational load when using the graph structure. Furthermore, we present a novel Active SLAM framework which outperforms traditional methods by successfully leveraging the graphical facet of the problem so as to autonomously explore an unknown environment.
@article{arxiv.2204.10610,
title = {Fast Autonomous Robotic Exploration Using the Underlying Graph Structure},
author = {Julio A. Placed and José A. Castellanos},
journal= {arXiv preprint arXiv:2204.10610},
year = {2022}
}
Comments
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). arXiv admin note: text overlap with arXiv:2110.01289