Abstract
In virtual production planning, simulating human motions helps to improve process planning and interaction efficiency. However, simulating multiple humans sharing tasks in a shared workplace requires understanding how human workers interact and share autonomy. In this regard, an Inertial Measurement Unit based motion capture is employed for understanding shifting roles and learning effects. Parameters such as total time, distance, and acceleration variances in repetition are considered for modeling collaborative motion interactions. The results distinguish motion patterns versus the undertaken interactions. This work may serve as an initial input to model interaction schemes and recognize human actions behavior during team assembly. Furthermore, the concept can be extended toward a human-robot shared autonomy.
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Acknowledgments
The authors would like to acknowledge the financial support by the Federal Ministry of Education and Research of Germany within the ITEA3 project MOSIM (grant number: 01IS18060AH), and by the European Regional Development Fund (EFRE) within the project SMAPS (grant number: 0200545).
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Tuli, T.B., Manns, M., Jonek, M. (2022). Understanding Shared Autonomy of Collaborative Humans Using Motion Capture System for Simulating Team Assembly. In: Andersen, AL., et al. Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems. CARV MCPC 2021 2021. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-90700-6_59
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