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This work presents a novel mapping approach to enable robotic refurbishment in both, regular as well as low visibility conditions. The computation is split in three modules: map creation in regular visibility conditions, semantic map augmentation, and map creation in low visibility environments. The obtained maps provide a lightweight visualization of all inferred semantic information and enable the navigation of the mobile unit as well as the planning and fulfillment of refurbishment tasks.