Active Perception for Embodied Disambiguation

2026-08-11

AI Summary

This study addresses target ambiguity in embodied environments caused by insufficient physical evidence by proposing an active perception framework grounded in vision-language models. Treating active observation as the primary mechanism for information acquisition, the method unifies physical exploration and user interaction within a single disambiguation process, enabling robots to autonomously decide between executing active observations or querying users to clarify intent. Real-world experiments demonstrate that this framework effectively integrates environmental exploration with human-robot interaction, significantly enhancing both target disambiguation performance and task success rates in complex scenarios.

Abstract

Natural language provides robots with a flexible task interface, but target ambiguity in embodied environments arises not only from user intent; it can also result from missing taskrelevant physical evidence in the current observation. Existing interactive disambiguation methods primarily obtain additional information by asking the user, whereas occlusion, restricted viewpoints, unreadable text, and unobserved targets require the robot to actively change its observation. We propose an active-perception framework for embodied target disambiguation that uses active observation as the backbone for information acquisition and uses a vision-language model to decide, on the basis of accumulated visual evidence and interaction information, whether to continue observing, request clarification, or complete target selection. Active observation can both directly recover missing discriminative evidence and reveal object names, labels, and semantic attributes, thereby improving user clarification when it remains necessary. Real-robot experiments show that the framework combines physical information acquisition and userintent clarification within a unified embodied disambiguation process.

Problem

• Embodied Disambiguation
• Active Perception
• Target Ambiguity
• Missing Physical Evidence

Innovation

• Active Perception
• Embodied Disambiguation
• Vision-Language Model
• Active Observation
• Target Ambiguity