Moenck, KenoKenoMoenckPrünte, Philipp JulianPhilipp JulianPrünteDetermann, JonathanJonathanDetermannErlich, EidanEidanErlichPatki, DhananjayDhananjayPatkiBitte, FrankFrankBitteGomse, MartinMartinGomseSchüppstuhl, ThorstenThorstenSchüppstuhl2026-03-042026-03-04202618th CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2024 (2026)https://hdl.handle.net/11420/61840The digitalization of chaotic intralogistics and production processes, including, e.g., humans and otherwise dynamic or static, non-tracked assets, as in the case of lot size one and large-object production facilities, requires non-invasive sensor solutions. One approach is to equip already movable assets on the shopfloor with multimodal 2D/2.5D/3D optical sensor systems that perceive the surrounding environment – such a solution requires methods for sensor calibration, sensor fusion, localization, and mapping. Besides, to comply with data privacy regulations, data must be de-personalized. This work proposes a mobile, multimodal sensor system that passively monitors the surroundings, localizes itself, outputs depersonalized data online, and can recreate the environment as a geometric digital twin.en2212-827120269095Elsevierhttps://creativecommons.org/licenses/by-nc-nd/4.0/factory planningmanufacturing optimizationmonitoringvision-based perceptionTechnology::670: ManufacturingTechnology::629: Other Branches::629.8: Control and Feedback Control SystemsConference Paperhttps://doi.org/10.15480/882.1680610.1016/j.procir.2026.01.01710.15480/882.16806Conference Paper