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Rethinking Learned Occupancy in Autonomous Active Mapping with Observation-Gated Filtering

arXiv · AI, language, vision and robotics · article · Sep 8, 2026 · UTC

Autonomous 3D active mapping requires a space robot to choose where to sense while building the geometry needed for navigation. Learned occupancy completion extends spatial context beyond the current field of view, but one predicted map often serves two planning roles: it scores expected surface gain and constrains collision-free motion. Unsupported occupancy can therefore distort both where the robot looks and where it believes it can travel. We study this coupled interface in a controlled closed-loop benchmark by holding the active-mapping system fixed and varying only its planner-facing occ

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