基于模式切换的多机器人异步协作自动扫描场景重建
Asynchronous Collaborative Autoscanning with Mode Switching for Multi-Robot Scene Reconstruction
摘要：
在对未知室内环境进行在线重建的自主扫描时，机器人必须能够探索场景结构并高质量地重建物体。我们的关键观察是，不同的任务需要专门的扫描性能的机器人：快速移动速度和远的全局探索和缓慢移动速度和局部对象重建，这被称为两种不同的扫描模式：探索者和重建器，分别视野狭窄。当需要多个机器人协作进行有效探索和细粒度重建时，应该仔细回答何时生成以及如何分配这些任务的问题。为此，提出了一种带模式切换的异步协作自动扫描方法，该方法生成两种具有相关扫描模式的扫描任务，探测任务采用探测器模式，重建任务采用重建器模式，并将其分配给机器人以异步协作的方式执行，以极大地提高扫描效率和重建质量。通过求解一个改进的多仓库多旅行商问题（MDMTSP）来优化任务分配。此外，为了进一步增强协作和提高效率，我们提出了一个任务流模型，该模型在任何机器人完成所有任务时立即激活任务生成和分配过程，而无需等待所有其他机器人完成上一次迭代中分配的任务。大量的实验已经进行了显示我们的方法的每个关键组成部分的重要性和优于以前的方法在扫描效率和重建质量。
英文摘要：
When conducting autonomous scanning for the online reconstruction of unknown indoor environments, robots have to be competent at exploring scene structure and reconstructing objects with high quality. Our key observation is that different tasks demand specialized scanning properties of robots: rapid moving speed and far vision for global exploration and slow moving speed and narrow vision for local object reconstruction, which are referred as two different scanning modes: explorer and reconstructor, respectively. When requiring multiple robots to collaborate for efficient exploration and fine-grained reconstruction, the questions on when to generate and how to assign those tasks should be carefully answered. Therefore, we propose a novel asynchronous collaborative autoscanning method with mode switching, which generates two kinds of scanning tasks with associated scanning modes, i.e., exploration task with explorer mode and reconstruction task with reconstructor mode, and assign them to the robots to execute in an asynchronous collaborative manner to highly boost the scanning efficiency and reconstruction quality. The task assignment is optimized by solving a modified Multi-Depot Multiple Traveling Salesman Problem (MDMTSP). Moreover, to further enhance the collaboration and increase the efficiency, we propose a task-flow model that actives the task generation and assignment process immediately when any of the robots finish all its tasks with no need to wait for all other robots to complete the tasks assigned in the previous iteration. Extensive experiments have been conducted to show the importance of each key component of our method and the superiority over previous methods in scanning efficiency and reconstruction quality.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
