Vision-Based Robot Manipulation of Transparent Liquid Containers in a Laboratory Setting

Laboratory processes involving small volumes of solutions and active ingredients are often performed man- ually 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 ap- proach 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 re- producible: 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.