At the footwear warehouse of logistics service provider Fiege, autonomous robots pick online orders.
Since September 2016, logistics service provider Fiege has been employing three Toru Cube mobile robots at its footwear warehouse in Ibbenbüren, Germany, to pick online orders. Using its laser and camera system, the perception-controlled, network-connected robot from Munich-based start-up Magazino can autonomously localise and identify individual objects on shelves, pick them, and then transport them to their intended destination.
Flexible working with no rigid programme
Jens Fiege, Executive of the family business of the same name, comments: “Our aim in deploying new technologies is always to make our logistics processes faster and more efficient.” In fulfilling those aims, the robots the company operates possess a high degree of autonomy. When a robot sets off on a job, it does not yet know in detail what it is going to do, but instead decides on the way to its destination. Only once it is close enough to the storage location to actually see the ordered shoes does it make the final adjustments. It determines the position of the box, and from it derives its subsequent actions. Essentially, the robot does not follow a rigid programme, but rather applies a set of rules governing its behaviour which tell it what action is required under specific given conditions.
Robot detects individual objects
A further special feature of the picking robot is that it is not only able to pick complete load carriers, such as pallets, from the shelf, but even individual product items. Its laser sensors and 3D camera system enable it to autonomously detect individual objects on the shelf. Magazino has developed a proprietary object recognition method for the purpose. The system, known as Sheet-of-Light, projects a cross laser comprising two perpendicular laser lines onto the object it is detecting. A 2D camera captures the reflected laser beams and gauges the object based on the position of the lines in the camera image. The method is designed for cuboid objects. Curved surfaces, such as the spines of books, can also be detected. Fewer 3D points are generated than with a 3D camera, so much less computing power is required, meaning the algorithm can be run on a mini-computer for example.
“Our aim in the deploying new technologies is always to make our logistics processes faster and more efficient”
Jens Fliege, Executive, Fliege Logistik
Humans and robots working in parallel
Frederik Brantner, Co-founder and Commercial Director of Magazino, stresses: “It was important right from the beginning that the robots should be able to work in parallel with people. That means part of the picking process can be automated in a flexible, gradual way.” Its safety laser enables the robot to detect not only obstacles in its way but also human employees around it, while also orientating itself within the warehouse. There is no need for reflectors or marker lines on the warehouse floor. Once taught, the connected robot can also share with new robot “colleagues” self-created maps of its surroundings, as well as experience in handling specific objects or meeting particular challenges, by way of its wireless connectivity. The smart robot is not only capable of working with existing shelving systems, it can also adapt to new situations and changes within the warehouse.
(Picture Credits: Istockphoto: Martinina)