MARLIN: A Cloud Integrated Robotic Solution to Support Intralogistics in Retail

TL;DR

This paper introduces MARLIN, a cloud-integrated service robot for retail intralogistics that leverages semantic digital twins and advanced navigation algorithms to improve stocking efficiency and adaptability in real-world store environments.

Contribution

The paper presents MARLIN's integration with the K4R cloud platform, including a novel navigation algorithm for articulated tractor-trailers, enhancing autonomous retail logistics.

Findings

MARLIN effectively updates store digital twins through obstacle detection and classification.

The robot autonomously plans and executes replenishment tasks in various environments.

The new navigation algorithm outperforms proprietary solutions in confined spaces.

Abstract

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.