Relational Semantic Reasoning on 3D Scene Graphs for Open World Interactive Object Search

• URL: http://arxiv.org/abs/2603.05642v1
• Date: Thu, 05 Mar 2026 19:52:26 GMT
• Title: Relational Semantic Reasoning on 3D Scene Graphs for Open World Interactive Object Search
• Abstract summary: We introduce SCOUT: Scene Graph-Based Exploration with Learned Utility for Open-World Interactive Object Search.<n>SCOUT searches directly over 3D scene graphs by assigning utility scores to rooms, frontiers, and objects.<n>We present SymSearch, a scalable symbolic benchmark for evaluating semantic reasoning in interactive object search tasks.
• Score: 14.297888615008041
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Open-world interactive object search in household environments requires understanding semantic relationships between objects and their surrounding context to guide exploration efficiently. Prior methods either rely on vision-language embeddings similarity, which does not reliably capture task-relevant relational semantics, or large language models (LLMs), which are too slow and costly for real-time deployment. We introduce SCOUT: Scene Graph-Based Exploration with Learned Utility for Open-World Interactive Object Search, a novel method that searches directly over 3D scene graphs by assigning utility scores to rooms, frontiers, and objects using relational exploration heuristics such as room-object containment and object-object co-occurrence. To make this practical without sacrificing open-vocabulary generalization, we propose an offline procedural distillation framework that extracts structured relational knowledge from LLMs into lightweight models for on-robot inference. Furthermore, we present SymSearch, a scalable symbolic benchmark for evaluating semantic reasoning in interactive object search tasks. Extensive evaluations across symbolic and simulation environments show that SCOUT outperforms embedding similarity-based methods and matches LLM-level performance while remaining computationally efficient. Finally, real-world experiments demonstrate effective transfer to physical environments, enabling open-world interactive object search under realistic sensing and navigation constraints.

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