Knowing Where to Look: Interactive Object Search via Spatial-Semantic Fusion
Overview
This paper introduces a system that combines semantic intuition from vision-language models with geometric spatial awareness using Bayesian log-odds filtering to create a unified 3D voxel belief field. The system drives action selection for viewing, navigating, or interacting with objects on a bimanual mobile humanoid, demonstrating improved performance over existing geometry-only and language-model-based search methods.
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- arXiv Robotics — research abstractsSignalKnowing Where to Look: Interactive Object Search via Spatial-Semantic Fusion
This paper introduces a system that combines semantic intuition from vision-language models with geometric spatial awareness using Bayesian log-odds filtering to create a unified 3D voxel belief field. The system drives action selection for viewing, navigating, or interacting with objects on a bimanual mobile humanoid, demonstrating improved performance over existing geometry-only and language-model-based search methods.
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