Many modern robotic systems operate autonomously, however they often lack the ability to accurately analyze the environment and adapt to changing external conditions, while teleoperation systems often require special operator skills. In the field of laboratory automation, the number of automated processes is growing, however such systems are usually developed to perform specific tasks. In addition, many of the objects used in this field are transparent, making it difficult to analyze them using visual channels. The contributions of this work include the development of a robotic framework with autonomous mode for manipulating liquid-filled objects with different degrees of transparency in complex pose combinations. The conducted experiments demonstrated the robustness of the designed visual perception system to accurately estimate object poses for autonomous manipulation, and confirmed the performance of the algorithms in dexterous operations such as liquid dispensing. The proposed robotic framework can be applied for laboratory automation, since it allows solving the problem of performing non-trivial manipulation tasks with the analysis of object poses of varying degrees of transparency and liquid levels, requiring high accuracy and repeatability.

翻译：许多现代机器人系统能够自主运行，然而它们通常缺乏准确分析环境并适应外部条件变化的能力，而遥操作系统则往往需要操作员具备特殊技能。在实验室自动化领域，自动化流程的数量正在增长，但此类系统通常是为执行特定任务而开发的。此外，该领域中使用的许多物体是透明的，这使得通过视觉通道对其进行分析变得困难。本工作的贡献包括开发了一个具备自主模式的机器人框架，用于在复杂的位姿组合下操作装有液体且具有不同透明度的物体。所进行的实验证明了所设计的视觉感知系统在准确估计物体位姿以实现自主操作方面的鲁棒性，并验证了算法在液体分注等灵巧操作中的性能。所提出的机器人框架可应用于实验室自动化，因为它能够解决执行非平凡操作任务的问题，同时分析具有不同透明度及液位的物体位姿，这需要高精度和可重复性。