Nowadays most of the functions in construction machines are driver controlled. Even if the machine is driven by an worker with a high level of training and experience the work tasks are not performed optimally. An increasing tiredness of the driver during operation or insufficient comprehension of the process are only two reasons. Using (partly) automated features improves machine efficiency. Considering the complexity of system descriptions with a rising amount of processed data and the limited resources of the control units in the construction machines, calculations have to be outsourced. This is particularly the case when services like optimised path planning or parameter identification for analytic digging force models should be executed. With a suitable architecture it becomes possible to stepwise integrate automation starting from assistance functions to full automation.

The central research goal of this project is the stepwise automation for the digging process of an automated \textbf{Smart Loader}. Therefore a cloud-based system architecture for driver assistance controlling construction machine functions is created to send all information from the loader to the cloud and visualize it in an application. In the cloud a simulation model for the mapping of the wheel loader is used to test the efficiency of the task and the machine. When the algorithm on the machine is inefficient the cloud can change different parameters or the hole algorithm at runtime. Therefore exists a master controller on the \textbf{Smart Loader} which handle the communication from the loader interface to the cloud and change the configuration if needed. The application for visualisation show a Smart Metering approach for the Smart Loader to show the technological performance of the different working steps. The processed data should improve the feeling of the workers efficiency and help him to perform different working steps.

In the first phase of the project all tests are run at the hardware in the loop test bench to show the working of the underlying approach. For the second phase the concept will install on a 24t wheel loader from the "Institut für Fluidtechnik".

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Sebastian Götz
Letzte Änderung: 12.07.2016