The growing complexity of industrial plants, enormous advances in autonomous driving and an increasingly digitized world require a quickly rising amount of virtual planning and testing using three-dimensional simulations. In addition to the number of technical advances, the complexity of individual objects and scenarios is increasing, pushing the requirements on simulation technology to generate sufficient realistic data within limited time frames.
Simulation frameworks have their means to store the information necessary to represent the properties of all scenario entities – the simulation state - in their database. However, they lack simulation algorithm-dependent transformations and augmentations of the simulation state that allow maximizing calculation efficiency. This paper introduces a generalized formalism to describe these transformations and illustrates how they help to bring the simulation framework closer to a specialized simulation database that stores spatial information with a focus on performance - the spatial database.
Further, this paper demonstrates the advantages of the approach with the introduction of two concrete transformations. One targets the efficient representation of three-dimensional spatial relations for industrial robots while the other allows generating different levels of complexity in the definition of materials in the context of autonomous driving.
- spatial database
- simulation state transformation
- high performance
- digital twins
- three-dimensional scenarios