In this paper, we present the service robot MARLIN and its integration with
the K4R platform, a cloud system for complex AI applications in retail. At its
core, this platform contains so-called semantic digital twins, a semantically
annotated representation of the retail store. MARLIN continuously exchanges
data with the K4R platform, improving the robot's capabilities in perception,
autonomous navigation, and task planning. We exploit these capabilities in a
retail intralogistics scenario, specifically by assisting store employees in
stocking shelves. We demonstrate that MARLIN is able to update the digital
representation of the retail store by detecting and classifying obstacles,
autonomously planning and executing replenishment missions, adapting to
unforeseen changes in the environment, and interacting with store employees.
Experiments are conducted in simulation, in a laboratory environment, and in a
real store. We also describe and evaluate a novel algorithm for autonomous
navigation of articulated tractor-trailer systems. The algorithm outperforms
the manufacturer's proprietary navigation approach and improves MARLIN's
navigation capabilities in confined spaces.

该研究论文介绍了服务机器人 MARLIN 及其与零售业中的复杂人工智能应用的云系统 K4R 平台的整合；研究表明，MARLIN 利用 K4R 平台不断交换数据，从而提高其在感知、自主导航和任务规划方面的能力，并通过在零售物流场景中协助店员进行货架补货，不断更新零售店铺的数字化表示；此外，研究在模拟、实验室环境和实际店铺中进行，介绍并评估了一种用于自主导航的新算法，该算法优于制造商的专有导航方法，提高了 MARLIN 在狭小空间中的导航能力。