STILL participates in the IMOCO project for autonomous driving

The vision of autonomous transport vehicles in production halls and warehouses is set to become a reality through the European research project IMOCO (Intelligent Motion Control). On the German side, the project is led by the Hamburg intralogistics specialist STILL, a subsidiary of the KION Group. The project is scheduled to conclude in the fourth quarter of 2024.

(Hamburg) The vision of autonomous transport vehicles in production halls and warehouses is set to become a reality through the European research project IMOCO.

Transport vehicles that navigate fully autonomously through warehouses and production, analyze their surroundings, learn to “understand,” reliably detect obstacles and people, and avoid them while quickly and reliably transporting goods from one place to another – this still sounds like science fiction. However, this vision is set to become reality soon, according to the initiators of the European research project IMOCO.

To achieve this, four scenarios have been defined within the research project, characterized by digital twins and AI principles (machine learning/deep learning): intelligent navigation, picking up goods, transportation, and placement at the destination. “Such processes place very high demands on the processes and also on the vehicle. Therefore, we have sent our OPX iGo neo, a picker with intelligent features and capabilities that already come very close to the concept of this autonomous vehicle, into the project,” describes Ansgar Bergmann, responsible for the IMOCO project at STILL.

Highly sensitive sensors are needed

Current automated guided vehicles still reach their limits when it comes to moving fully autonomously in warehouses or production. While they can detect obstacles and brake independently, they cannot yet navigate around obstacles, intelligently search for the most efficient routes, and analyze their surroundings. They require highly sensitive sensors in the form of laser scanners, cameras, or radar to detect spatial objects such as shelves or signs, markings, and displays. Additionally, they must “understand” their environment, register changes, and be able to respond accordingly. Only then will these vehicles be able to navigate autonomously to their destination, recognize and handle loads, avoid obstacles, or find suitable parking spots for the transported goods.

Enhancing autonomous capabilities

The OPX iGo neo is already operating autonomously in the aisle, perceiving and understanding its environment and deriving its actions from it. However, leaving the aisle autonomously and navigating through the customer’s halls, for example, by planning optimal paths, is not yet part of the product. However, since it is already equipped with appropriate environmental sensors, this makes it an ideal starting point for the intended developments of this project. “For the OPX iGo neo, the goal of the project is to further increase the degree of understanding of the environment and the decision-making capabilities, thereby continuously enhancing the autonomous capabilities and intelligence of the robot, allowing it to operate autonomously beyond the aisle in the warehouse. Machine learning and deep learning approaches play a very important role in this,” explains Ansgar Bergmann.

Real-time obstacle detection

IMOCO aims to create the conditions for the challenging deployment of mobile robotic systems in dynamic intralogistics environments. Autonomous and situationally adaptive planning changes to a driving route, including consideration of moving objects such as people or vehicles, should then be possible throughout the warehouse. Ansgar Bergmann states: “The research project aims to further develop the traditional triad of recognizing, analyzing, and acting through artificial intelligence – to perceiving, understanding, and solving.” Within the research project, the vehicles are to be enabled to perceive the spatial environment through various sensors and not only recognize trained objects but also assess their movements. “This detection of obstacles must occur in real-time for a smooth operation,” says the expert.

Hamburg becomes a ‘Research Center’

A demonstrator is being set up at the STILL headquarters in Hamburg, where all the work successes of the project partners will be brought together. In addition to STILL as a representative of the KION Group, the Fraunhofer Institute for Material Flow and Logistics (IML), Hahn Schickard, IMST GmbH, Nuromedia, and Digital Twin Technology are also participating in the project on the German side. IMOCO is funded by the European Union through the research funding program “Electronic Components and Systems for European Leadership” (ECSEL) as well as by the Federal Ministry of Education and Research.

Photo: © STILL