OpenGraph：大规模室外环境中的开放词汇分层三维图表示
OpenGraph: Open-Vocabulary Hierarchical 3D Graph Representation in Large-Scale Outdoor Environments
AI总结：
本文提出OpenGraph，首个面向大规模室外环境的开放词汇分层三维图表示，通过实例提取、LiDAR点云特征嵌入和车道图连通性分割构建分层图，在SemanticKITTI上取得最优分割与查询精度。
摘要：
具备丰富语义的环境表示对于促进机器人与人类之间的无缝交互至关重要，能够使它们有效执行各种任务。由视觉-语言模型（VLMs）驱动的开放词汇地图具有固有优势，包括零样本学习和对开放集类别的支持。然而，现有的开放词汇地图主要针对小规模环境（如桌面或房间）设计，通常面向涉及机器人室内导航或原地操作的有限区域任务。由于理解水平和地图结构方面的限制，它们在直接泛化到具有众多物体和复杂任务的室外环境时面临挑战。在这项工作中，我们提出了OpenGraph，这是首个专为大规模室外环境设计的开放词汇分层图表示。OpenGraph首先从视觉图像中提取实例及其描述文本，通过对它们进行编码来增强文本推理。随后，通过将图像投影到LiDAR点云上，实现具有特征嵌入的三维增量式以对象为中心的建图。最后，基于车道图连通性对环境进行分割，以构建分层图。公开数据集SemanticKITTI的验证结果表明，OpenGraph实现了最高的分割和查询准确率。OpenGraph的源代码已在https://github.com/BIT-DYN/OpenGraph公开提供。
英文摘要：
Environment representations endowed with sophisticated semantics are pivotal for facilitating seamless interaction between robots and humans, enabling them to effectively carry out various tasks. Open-vocabulary maps, powered by Visual-Language models (VLMs), possess inherent advantages, including zero-shot learning and support for open-set classes. However, existing open-vocabulary maps are primarily designed for small-scale environments, such as desktops or rooms, and are typically geared towards limited-area tasks involving robotic indoor navigation or in-place manipulation. They face challenges in direct generalization to outdoor environments characterized by numerous objects and complex tasks, owing to limitations in both understanding level and map structure. In this work, we propose OpenGraph, the first open-vocabulary hierarchical graph representation designed for large-scale outdoor environments. OpenGraph initially extracts instances and their captions from visual images, enhancing textual reasoning by encoding them. Subsequently, it achieves 3D incremental object-centric mapping with feature embedding by projecting images onto LiDAR point clouds. Finally, the environment is segmented based on lane graph connectivity to construct a hierarchical graph. Validation results from public dataset SemanticKITTI demonstrate that OpenGraph achieves the highest segmentation and query accuracy. The source code of OpenGraph is publicly available at https://github.com/BIT-DYN/OpenGraph.
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。
