Autonomous construction machines are highly relevant for automation of the computational design and construction. Construction sites of the future demand for autonomous systems such as cranes, assembly robots, excavators, wheel loaders.
However, in this area of computational design and construction, it is difficult to generate real data sets for the complex scenarios of autonomous construction machines in order to develop and test the functionality. Synthetic data is required to create a sufficient number of scenarios, especially multiple test cases for the training of an AI and its functionality. In this project, synthetic data is created by simulating rare scenarios in a Co-Simulation system consisting of an environment- and construction machine simulation resulting in training, development and system test data sets.
Further information at IntCDC.