Deploying autonomous robots capable of exploring unknown environments has long been a topic of great relevance to the robotics community. In this work, we take a further step in that direction by presenting an open-source active visual SLAM framework that leverages the accuracy of a state-of-the-art graph-SLAM system and takes advantage of the fast utility computation that exploiting the structure of the underlying pose-graph offers. Through careful estimation of a posteriori weighted pose-graphs, D-optimal decision-making is achieved online with the objective of improving localization and mapping uncertainties as exploration occurs.
@article{arxiv.2209.03693,
title = {ExplORB-SLAM: Active Visual SLAM Exploiting the Pose-graph Topology},
author = {Julio A. Placed and Juan J. Gómez Rodríguez and Juan D. Tardós and José A. Castellanos},
journal= {arXiv preprint arXiv:2209.03693},
year = {2022}
}
Comments
12 pages. To be presented in 5th Iberian Robotics Conference