BEGIN:VCALENDAR VERSION:2.0 PRODID:Linklings LLC BEGIN:VTIMEZONE TZID:Asia/Seoul X-LIC-LOCATION:Asia/Seoul BEGIN:STANDARD TZOFFSETFROM:+0900 TZOFFSETTO:+0900 TZNAME:KST DTSTART:18871231T000000 DTSTART:19881009T020000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20230103T035306Z LOCATION:Auditorium\, Level 5\, West Wing DTSTART;TZID=Asia/Seoul:20221206T100000 DTEND;TZID=Asia/Seoul:20221206T120000 UID:siggraphasia_SIGGRAPH Asia 2022_sess153_papers_344@linklings.com SUMMARY:Asynchronous Collaborative Autoscanning with Mode Switching for Mu lti-Robot Scene Reconstruction DESCRIPTION:Technical Papers\n\nAsynchronous Collaborative Autoscanning wi th Mode Switching for Multi-Robot Scene Reconstruction\n\nGuo, Li, Xia, Hu , Liu\n\nWhen 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 s low moving speed and narrow vision for local object reconstruction, which are referred as two different scanning modes: scout and raider, respective ly. When further requiring multiple robots to collaborate for efficient ex ploration and fine-grained reconstruction, we study the questions on when to generate and how to assign those tasks. Therefore, we propose a novel a synchronous collaborative autoscanning method with mode switching, which g enerates 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 collaborativ e manner to highly boost the scanning efficiency and reconstruction qualit y. Those generated tasks are assigned to the robots by solving a modified Multi-Depot Multiple Traveling Salesman Problem (MDMTSP). Moreover, to fur ther enhance the collaboration and increase the efficiency, we propose a t ask-flow model that actives the task generation and assignment process imm ediately when any of the robots finishes all its tasks with no need to wai t for all other robots to complete the tasks assigned in the previous iter ation. Extensive experiments have been conducted to show the importance of each key component of our method and the superiority of our method over p revious methods in scanning efficiency and reconstruction quality.\n\nRegi stration Category: FULL ACCESS, EXPERIENCE PLUS ACCESS, EXPERIENCE ACCESS, TRADE EXHIBITOR\n\nLanguage: ENGLISH\n\nFormat: IN-PERSON URL:https://sa2022.siggraph.org/en/full-program/?id=papers_344&sess=sess15 3 END:VEVENT END:VCALENDAR