Abstract
Digital human simulation is important for various domains such as the entertainment, health care and production industries. A variety of simulation techniques and tools are available, ranging from motion-capture-based animation systems and deep learning to physics-based motion synthesis. Each technology has its advantages and disadvantages and is suited for particular use cases. Therefore, a combination of multiple technologies would result in more sophisticated simulations, which can address heterogeneous aspects. However, the different approaches are mostly tightly coupled with the development environment, thus inducing high porting efforts if being incorporated into different platforms. A combination of separately developed simulation systems either for benchmarking or comprehensive simulation is not possible yet. For the domain of plant simulation, the Functional Mock-up Interface (FMI) standard has already solved this problem. Initially being tailored to industrial needs, the standards allow exchanging dynamic simulation approaches such as solvers for mechatronic components. Inspired by the FMI standard, we present a novel framework to incorporate multiple digital human simulation approaches from multiple domains. In particular, the paper introduces the overall concept of the so-called Motion Model Units, as well as its underlying technical architecture. As main contribution, a novel co-simulation for the orchestration of multiple digital human simulation approaches is presented. The overall applicability is approved based on a quantitative evaluation using motion capture data and a user study.















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Acknowledgements
The authors acknowledge the financial support by the Federal Ministry of Education and Research of Germany within the MOSIM Project [19] (Grant No. 01IS18060A-H).
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Gaisbauer, F., Lampen, E., Agethen, P. et al. Combining heterogeneous digital human simulations: presenting a novel co-simulation approach for incorporating different character animation technologies. Vis Comput 37, 717–734 (2021). https://doi.org/10.1007/s00371-020-01792-x
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DOI: https://doi.org/10.1007/s00371-020-01792-x