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Computer Science > Robotics

arXiv:2506.01950 (cs)
[Submitted on 2 Jun 2025 (v1) , last revised 13 Aug 2025 (this version, v3)]

Title: DualMap: Online Open-Vocabulary Semantic Mapping for Natural Language Navigation in Dynamic Changing Scenes

Title: DualMap:动态变化场景中自然语言导航的在线开放词汇语义地图

Authors:Jiajun Jiang, Yiming Zhu, Zirui Wu, Jie Song
Abstract: We introduce DualMap, an online open-vocabulary mapping system that enables robots to understand and navigate dynamically changing environments through natural language queries. Designed for efficient semantic mapping and adaptability to changing environments, DualMap meets the essential requirements for real-world robot navigation applications. Our proposed hybrid segmentation frontend and object-level status check eliminate the costly 3D object merging required by prior methods, enabling efficient online scene mapping. The dual-map representation combines a global abstract map for high-level candidate selection with a local concrete map for precise goal-reaching, effectively managing and updating dynamic changes in the environment. Through extensive experiments in both simulation and real-world scenarios, we demonstrate state-of-the-art performance in 3D open-vocabulary segmentation, efficient scene mapping, and online language-guided navigation.Project page: https://eku127.github.io/DualMap/
Abstract: 我们引入了DualMap,这是一种在线开放词汇映射系统,使机器人能够通过自然语言查询理解并导航动态变化的环境。 设计用于高效的语义映射和适应变化的环境,DualMap满足实际机器人导航应用的基本要求。 我们提出的混合分割前端和对象级状态检查消除了先前方法所需的昂贵的3D对象合并,实现了高效的在线场景映射。 双图表示结合了一个全局抽象地图用于高层候选选择和一个局部具体地图用于精确的目标到达,有效地管理和更新环境中的动态变化。 通过在仿真和真实世界场景中的大量实验,我们展示了在3D开放词汇分割、高效场景映射和在线语言引导导航方面的最先进性能。项目页面:https://eku127.github.io/DualMap/
Comments: 14 pages, 14 figures. Code: https://github.com/Eku127/DualMap Project page: https://eku127.github.io/DualMap/
Subjects: Robotics (cs.RO) ; Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2506.01950 [cs.RO]
  (or arXiv:2506.01950v3 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2506.01950
arXiv-issued DOI via DataCite

Submission history

From: Jiajun Jiang [view email]
[v1] Mon, 2 Jun 2025 17:59:10 UTC (7,269 KB)
[v2] Wed, 4 Jun 2025 17:05:36 UTC (6,595 KB)
[v3] Wed, 13 Aug 2025 07:21:25 UTC (17,544 KB)
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