Vision-based robot manipulation of transparent liquid containers in a laboratory setting
Daniel Schober, Ronja Güldenring, James Love, Lazaros Nalpantidis
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- github.com/danischober/labliquidvisionOfficialIn paperpytorch★ 19
Abstract
Laboratory processes involving small volumes of solutions and active ingredients are often performed manually due to challenges in automation, such as high initial costs, semi-structured environments and protocol variability. In this work, we develop a flexible and cost-effective approach to address this gap by introducing a vision-based system for liquid volume estimation and a simulation-driven pouring method particularly designed for containers with small openings. We evaluate both components individually, followed by an applied real-world integration of cell culture automation using a UR5 robotic arm. Our work is fully reproducible: we share our code at at https://github.com/DaniSchober/LabLiquidVision and the newly introduced dataset LabLiquidVolume is available at https://data.dtu.dk/articles/dataset/LabLiquidVision/25103102.