HERO: Hierarchical Traversable 3D Scene Graphs for Embodied Navigation Among Movable Obstacles
Yunheng Wang, Yixiao Feng, Yuetong Fang, Shuning Zhang, Tan Jing, Jian Li, Xiangrui Jiang, Renjing Xu

TL;DR
HERO introduces a hierarchical 3D scene graph framework that models movable obstacles as traversable pathways, significantly improving navigation efficiency and reachability in complex environments for embodied agents.
Contribution
The paper presents HERO, a novel hierarchical 3D scene graph approach that redefines traversability by incorporating movable obstacles as pathways, enabling better reasoning and planning.
Findings
PL reduced by 35.1% in partially obstructed environments
SR increased by 79.4% in fully obstructed environments
Enhanced efficiency and reachability in complex scenes
Abstract
3D Scene Graphs (3DSGs) constitute a powerful representation of the physical world, distinguished by their abilities to explicitly model the complex spatial, semantic, and functional relationships between entities, rendering a foundational understanding that enables agents to interact intelligently with their environment and execute versatile behaviors. Embodied navigation, as a crucial component of such capabilities, leverages the compact and expressive nature of 3DSGs to enable long-horizon reasoning and planning in complex, large-scale environments. However, prior works rely on a static-world assumption, defining traversable space solely based on static spatial layouts and thereby treating interactable obstacles as non-traversable. This fundamental limitation severely undermines their effectiveness in real-world scenarios, leading to limited reachability, low efficiency, and inferior…
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Taxonomy
TopicsMultimodal Machine Learning Applications · Robotics and Sensor-Based Localization · Robotic Path Planning Algorithms
