OpenObject-NAV: Open-Vocabulary Object-Oriented Navigation Based on Dynamic Carrier-Relationship Scene Graph

  • Yujie Tang
  • , Meiling Wang
  • , Yinan Deng
  • , Zibo Zheng
  • , Jiagui Zhong
  • , Tiancheng Liu
  • , Chenjie Zhao
  • , Yufeng Yue*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In everyday life, frequently used objects like cups often have unfixed positions and multiple instances within the same category, and their carriers frequently change as well. As a result, it becomes challenging for a robot to efficiently navigate to a specific instance. To tackle this challenge, the robot must capture and update scene changes and plans continuously. However, current object navigation approaches primarily focus on the semantic level and lack the ability to dynamically update scene representation. To address these limitations, this paper captures the relationships between frequently used objects and their static carriers. Specifically, it constructs an open-vocabulary Carrier-Relationship Scene Graph (CRSG) and updates the carrying status during robot navigation to reflect the dynamic changes of the scene. Based on the CRSG, we further propose an instance navigation strategy that models the navigation process as a Markov Decision Process. At each step, decisions are informed by Large Language Model's commonsense knowledge and visual-language feature similarity. We designed a series of long-sequence navigation tasks for frequently used everyday items in the Habitat simulator. The results demonstrate that by updating the CRSG, the robot can efficiently navigate to moved targets. Additionally, we deployed our algorithm on a real robot and validated its practical effectiveness. The project page can be found here: https://OpenObject-Nav.github.io.

Original languageEnglish
Title of host publicationIROS 2025 - 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, Conference Proceedings
EditorsChristian Laugier, Alessandro Renzaglia, Nikolay Atanasov, Stan Birchfield, Grzegorz Cielniak, Leonardo De Mattos, Laura Fiorini, Philippe Giguere, Kenji Hashimoto, Javier Ibanez-Guzman, Tetsushi Kamegawa, Jinoh Lee, Giuseppe Loianno, Kevin Luck, Hisataka Maruyama, Philippe Martinet, Hadi Moradi, Urbano Nunes, Julien Pettre, Alberto Pretto, Tommaso Ranzani, Arne Ronnau, Silvia Rossi, Elliott Rouse, Fabio Ruggiero, Olivier Simonin, Danwei Wang, Ming Yang, Eiichi Yoshida, Huijing Zhao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages20182-20188
Number of pages7
ISBN (Electronic)9798331543938
DOIs
Publication statusPublished - 2025
Externally publishedYes
Event2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2025 - Hangzhou, China
Duration: 19 Oct 202525 Oct 2025

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2025
Country/TerritoryChina
CityHangzhou
Period19/10/2525/10/25

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