Abstract
We formulate and solve an inverse optimal control problem that allows us to study human gait based on motion capture data and a template model that is defined by a simple mechanical model of walking with two elastic legs. To this end we derive an optimal control model that consists of two parts: a three-dimensional template walker and an objective, defined by a linear combination of physically meaningful optimization criteria known from humanoid robotics. Based on a direct all-at-once approach we identify the objective weights such that the resulting optimal gait fits real human motion data as closely as possible. Considering knee actuation, foot placement and phase duration as controls we identify the optimal weights for six different trials on level ground from two very different subjects. In future work the identified criteria will be used to simulate optimized human gait and to generate reference trajectories for humanoid gait control.
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Acknowledgements
The research leading to these results has received funding from the European Union Seventh Framework Program (FP7/2007–2013) under grant agreement no 611909 (KoroiBot). We wish to thank the Simulation and Optimization group of H. G. Bock at the University of Heidelberg for providing the optimal control code MUSCOD and K. Hatz for providing the code ParaOCP. Furthermore we want to thank M. Giese and co-workers, University Tübingen, for collecting the motion capture data used in this work. The data is published in the KoroiBot database set up by T. Asfour and co-workers, KIT, Karlsruhe. Finally, we also would like to thank the anonymous reviewers for their helpful comments.
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Clever, D., Mombaur, K. (2017). On the Relevance of Common Humanoid Gait Generation Strategies in Human Locomotion: An Inverse Optimal Control Approach. In: Bock, H., Phu, H., Rannacher, R., Schlöder, J. (eds) Modeling, Simulation and Optimization of Complex Processes HPSC 2015 . Springer, Cham. https://doi.org/10.1007/978-3-319-67168-0_3
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DOI: https://doi.org/10.1007/978-3-319-67168-0_3
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