Asynchronous Collaborative Autoscanning with Mode Switching for Multi-Robot Scene Reconstruction
DescriptionWhen conducting autonomous scanning for the online reconstruction of unknown indoor environments, robots have to be competent at exploring the 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: scout and raider, respectively. When further requiring multiple robots to collaborate for efficient exploration and fine-grained reconstruction, we study the questions on when to generate and how to assign those tasks. 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 scout mode and reconstruction task with raider mode, and assign them to the robots to execute in an asynchronous collaborative manner to highly boost the scanning efficiency and reconstruction quality. Those generated tasks are assigned to the robots 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 finishes 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 of our method over previous methods in scanning efficiency and reconstruction quality.
Event Type
Technical Papers
TimeWednesday, 7 December 202211:00am - 12:30pm KST
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