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HSG-ON: Hierarchical Scene Graph-Based Object Navigation.

Seokjoon Kwon1, Hee-Deok Jang1, Dong Eui Chang1

  • 1School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.

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Summary

Robots can now find unseen objects in new environments using a novel hierarchical scene graph. This system enhances zero-shot object goal navigation by improving search efficiency and success rates.

Keywords:
embodied aihierarchical scene graphlarge language modellarge vision language modelroboticszero-shot object goal navigation

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Vision

Background:

  • Robots require effective object recognition in human environments.
  • Zero-shot object goal navigation is challenging due to the need to find unseen objects in novel settings without prior data.
  • Current exploration strategies in robotics can be inefficient.

Purpose of the Study:

  • To develop an improved system for zero-shot object goal navigation.
  • To enhance robot exploration strategies for greater efficiency and success.

Main Methods:

  • A hierarchical scene graph navigation system was developed.
  • A three-layer "room-workspace-object" scene graph is dynamically constructed without manual parameter tuning.
  • A workspace-based searching strategy evaluates semantic relevance at the workspace level to infer probable object containers.

Main Results:

  • The proposed system significantly outperforms existing state-of-the-art methods in simulations.
  • Success Rate (SR) improved by 26.8% (SR 0.4859) under distance constraints.
  • SR improved by 20.2% (SR 0.7360) under unconstrained settings.

Conclusions:

  • The hierarchical scene graph system offers a robust solution for zero-shot object goal navigation.
  • The workspace-based search strategy enables more focused and human-like exploration.
  • This approach addresses limitations in strategic exploration for robotic navigation.