MARLIN: A Cloud Integrated Robotic Solution to Support Intralogistics in Retail
This addresses the challenge of automating repetitive tasks in retail logistics for store employees, but it is incremental as it builds on existing robotic and cloud technologies.
The paper tackles the problem of automating retail intralogistics by presenting MARLIN, a service robot integrated with a cloud platform to assist in stocking shelves, demonstrating capabilities in obstacle detection, autonomous navigation, and task planning in simulated, lab, and real-store experiments.
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.