Siemens Aktiengesellschaft

Axel Walthelm

Thomas Dobler

Fabricio De Carvalho Ferreira

Julian Vogel

Johannes Benkert

In a method for a collision-free movement of a crane in a crane lane, a sensor captures a first training data set of raw data during a movement of the crane outside a crane operation in the crane lane. The first training data set is evaluated while teaching a first neural network based on the captured raw data and first training data are determined from the evaluated first training data set. The sensor captures current sensor data during a movement of the crane during the crane operation in the crane lane. The current sensor data is compared with the first training data, and an anomaly is detected between the current sensor data and the first training data.

Method for the collision-free movement of a crane

A container crane has a trolley movable on a cross-member of a gantry. A harness for picking up and setting down a container and at least one laser scanner are arranged on the trolley. The laser scanner captures a depth image which, as a function of a first and a second angle, indicates the distance of object points detected by a laser beam. The captured depth image is evaluated. Based on the object points, objects are detected and their locations are determined. The objects comprise the harness and/or a container picked up by the harness, and further objects. Based on the detected object points, the contour of the harness and/or of the container picked up by the harness is determined. Detection of further objects within regions defined by the contour is suppressed. A control device takes the detected objects and their locations into account for controlling the container crane.

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Buckenhof, Germany

Axel Walthelm