Collaborative Instance Object Navigation: Leveraging Uncertainty-Awareness to Minimize Human-Agent Dialogues [ICCV 25]

🎉 ICCV 2025 - Project Page 🎉

Francesco Taioli, Edoardo Zorzi, Gianni Franchi, Alberto Castellini, Alessandro Farinelli, Marco Cristani, Yiming Wang

---

Abstract

Existing embodied instance goal navigation tasks, driven by natural language, assume human users to provide complete and nuanced instance descriptions prior to the navigation, which can be impractical in the real world as human instructions might be brief and ambiguous. To bridge this gap, we propose a new task, Collaborative Instance Navigation (CoIN), with dynamic agent-human interaction during navigation to actively resolve uncertainties about the target instance in natural, template-free, open-ended dialogues. To address CoIN, we propose a novel method, Agent-user Interaction with UncerTainty Awareness (AIUTA), leveraging the perception capability of Vision Language Models (VLMs) and the capability of Large Language Models (LLMs). First, upon object detection, a Self-Questioner model initiates a self-dialogue to obtain a complete and accurate observation description, while a novel uncertainty estimation technique mitigates inaccurate VLM perception. Then, an Interaction Trigger module determines whether to ask a question to the user, continue or halt navigation, minimizing user input. For evaluation, we introduce CoIN-Bench, a benchmark supporting both real and simulated humans. AIUTA achieves competitive performance in instance navigation against state-of-the-art methods, demonstrating great flexibility in handling user inputs.

Table of contents

Release timeline:

• AIUTA (upon acceptance)
  • Multimodal Uncertainty Estimation (notebook folder)
• CoIN-Bench (upon acceptance)
• IDKVQA dataset (upon acceptance)

Quick start

Multimodal Uncertainty Estimation

In the notebook folder, run perception_uncertainty_estimation.ipynb for a quick, well-commented example of multimodal uncertainty estimation.

Website License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. (Website branch)