DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jang, Seoyeon | ko |
dc.contributor.author | OH, MINHO | ko |
dc.contributor.author | YU, BYEONGHO | ko |
dc.contributor.author | Nahrendra, I Made Aswin | ko |
dc.contributor.author | Lee, Seungjae | ko |
dc.contributor.author | Lim, HyungTae | ko |
dc.contributor.author | Myung, Hyun | ko |
dc.date.accessioned | 2024-01-04T01:01:35Z | - |
dc.date.available | 2024-01-04T01:01:35Z | - |
dc.date.created | 2024-01-03 | - |
dc.date.issued | 2023-12-06 | - |
dc.identifier.citation | International Conference on Robot Intelligence Technology and Applications (RiTA 2023) | - |
dc.identifier.uri | http://hdl.handle.net/10203/317323 | - |
dc.description.abstract | Safe navigation with simultaneous localization and mapping (SLAM) for autonomous robots is crucial in challenging environments. To achieve this goal, detecting moving objects in the surroundings and building a static map are essential. However, existing moving object segmentation methods have been developed separately for each field, making it challenging to perform real-time navigation and precise static map building simultaneously. In this paper, we propose an integrated real-time framework that combines online tracking-based moving object segmentation with static map building. For safe navigation, we introduce a computationally efficient hierarchical association cost matrix to enable real-time moving object segmentation. In the context of precise static mapping, we present a voting-based method, DS-Voting, designed to achieve accurate dynamic object removal and static object recovery by emphasizing their spatio-temporal differences. We evaluate our proposed method quanti-tatively and qualitatively in the SemanticKITTI dataset and real-world chal-lenging environments. The results demonstrate that dynamic objects can be clearly distinguished and incorporated into static map construction, even in stairs, steep hills, and dense vegetation. | - |
dc.language | English | - |
dc.publisher | SPRINGER INTERNATIONAL PUBLISHING AG | - |
dc.title | TOSS: Real-time Tracking and Moving Object Segmentation for Static Scene Mapping | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | International Conference on Robot Intelligence Technology and Applications (RiTA 2023) | - |
dc.identifier.conferencecountry | CC | - |
dc.identifier.conferencelocation | Taicang | - |
dc.contributor.localauthor | Myung, Hyun | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.