论文标题
D-lite：用于多机器人协作的3D场景图的导航压缩
D-Lite: Navigation-Oriented Compression of 3D Scene Graphs for Multi-Robot Collaboration
论文作者
论文摘要
对于一个合作探索未知环境的多机器人团队，至关重要的是，收集的信息在机器人之间有效共享以支持勘探和导航任务。无线通道的实际限制（例如有限的带宽）敦促机器人仔细选择要传输的信息。在本文中，我们考虑了使用3D场景图对环境信息进行建模的情况，这是描述环境的几何和语义方面的层次图表示。然后，我们利用图理论工具，即图形跨度，以设计有效压缩3D场景图的贪婪算法，目的是在带宽约束下启用机器人之间的通信。我们的压缩算法以导航为导向，因为它们旨在在感兴趣的位置之间几乎保留最短的路径，同时满足用户指定的通信预算约束。在逼真的模拟器中的合成机器人导航实验中证明了所提出的算法的有效性。可以在https://youtu.be/nkyxu5vc6a8上找到视频摘要。
For a multi-robot team that collaboratively explores an unknown environment, it is of vital importance that collected information is efficiently shared among robots in order to support exploration and navigation tasks. Practical constraints of wireless channels, such as limited bandwidth, urge robots to carefully select information to be transmitted. In this paper, we consider the case where environmental information is modeled using a 3D Scene Graph, a hierarchical map representation that describes both geometric and semantic aspects of the environment. Then, we leverage graph-theoretic tools, namely graph spanners, to design greedy algorithms that efficiently compress 3D Scene Graphs with the aim of enabling communication between robots under bandwidth constraints. Our compression algorithms are navigation-oriented in that they are designed to approximately preserve shortest paths between locations of interest, while meeting a user-specified communication budget constraint. The effectiveness of the proposed algorithms is demonstrated in synthetic robot navigation experiments in a realistic simulator. A video abstract is available at https://youtu.be/nKYXU5VC6A8.
