Just-In-Time Scene Graph Growth: Combating Perceptual Saturation in Long-Horizon Robotics

• URL: http://arxiv.org/abs/2607.13245v1
• Date: Tue, 14 Jul 2026 20:14:50 GMT
• Title: Just-In-Time Scene Graph Growth: Combating Perceptual Saturation in Long-Horizon Robotics
• Abstract summary: We present JITOMA, a closed-loop framework that unifies task reasoning, perception, and memory into a just-in-time growth process.<n>We show that JITOMA substantially reduces active graph size and captioning latency, while maintaining stable processing time under longhorizon task switching.
• Score: 25.314200952645567
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: While 3D Scene Graphs (3DSGs) provide crucial structured representations for embodied agents, conventional Ahead-of-Time, build-everything-then-filter pipelines conflict with the real-time, low-latency demands of edge platforms, inducing a perceptual saturation effect via severe observation redundancy. To resolve this, we present JITOMA (Just-In-Time On-demand Memory Activation), a closed-loop framework that unifies task reasoning, perception, and memory into a just-in-time growth process. Instead of exhaustively mapping the entire environment, JITOMA leverages a top-down task heatmap at the frontend to filter continuous observations, routing minimal streams to maintain a global foundation of low-cost, dormant anchors. Upon a cognitive query, the backend Large Language Model (LLM) parses the robotic intent to dynamically awaken task-relevant anchors, triggering resource-intensive operations -- such as dense node captioning and functional inference -- exclusively within the activated local subgraph. To evaluate these dynamic capabilities and study perceptual saturation trade-offs, we introduce JITOMA-Bench, a comprehensive suite for long-horizon multi-tasking and complex multi-step reasoning. Extensive experiments demonstrate that JITOMA substantially reduces active graph size and captioning latency, while maintaining stable processing time under long-horizon task switching.

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