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KRVF: A Source-Aware Semantic Voxel World Representation for Edge Mobile Manipulation
[Submitted on 24 Jun 2026] · 2026-06-26 · via cs updates on arXiv.org

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Abstract:Mobile manipulators need world models that are current, queryable, semantically meaningful, and usable under edge-compute constraints. This technical report presents KRVF, a source-aware semantic voxel world representation for edge mobile manipulation. Unlike reconstruction-centric mapping pipelines that primarily optimize global geometric fidelity, KRVF represents local world state as task-oriented voxels that encode occupancy, color, semantic evidence, temporal freshness, and evidence source. The representation separates measured occupancy from semantic-prior hypotheses, enabling depth-failure-aware object reasoning without silently corrupting persistent geometry. KRVF also closes a feedback loop between mapping and sensing by rendering map-prior depth for repair, and exposes task-level query operators for semantic objects and grasp candidates. The report formalizes the KRVF representation and documents a ROS 2 implementation that turns online RGB-D observations into a task-facing robot memory.

Submission history

From: Runfeng Ling [view email]
[v1] Wed, 24 Jun 2026 19:07:42 UTC (1,721 KB)

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