论文标题
Explorb-slam：主动视觉大满贯利用姿势图形拓扑
ExplORB-SLAM: Active Visual SLAM Exploiting the Pose-graph Topology
论文作者
论文摘要
长期以来，部署能够探索未知环境的自动机器人一直是与机器人社区具有很大相关性的话题。在这项工作中，我们通过提出一个开源的主动视觉大满贯框架来朝着这个方向迈出一步，该框架利用了最先进的图形链接系统的准确性，并利用了利用基础姿势图提供的结构的快速效用计算。通过仔细估算后验加权姿势图，在网上实现了D-最佳决策，目的是在发生探索时改善本地化和映射不确定性。
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.
