论文标题
使用底层图结构的快速自主机器人探索
Fast Autonomous Robotic Exploration Using the Underlying Graph Structure
论文作者
论文摘要
在这项工作中，我们充分定义了主动大满贯中基础姿势图之间的现有关系，因此表征了图理论与理论最佳实验设计之间的联系。我们验证了2D和3D Graph SLAM数据集中提出的关系，在使用图形结构时显示了计算负载的显着放松。此外，我们提出了一个新颖的主动SLAM框架，该框架通过成功利用问题的图形方面以自主探索未知环境来超越传统方法。
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.
