Abstract
In this paper a problem of controlling a lower limb exoskeleton during sit-to-stand motion (verticalization) in sagittal plane is studied. It is assumed that left and right sides of the exoskeleton are moving symmetrically. The main challenge in performing this motion is to maintain balance of the system. In this paper we use the zero-moment point (ZMP) methodology to produce desired trajectories for the generalized coordinates that would allow the system to remain vertically balanced. The limitations of this approach is that, it requires relatively accurate work of the feedback controller that ensures that the exoskeleton follows generated trajectories. In this work we use Iterative Linear Quadratic Regulator (ILQR) as a feedback controller in order to obtained the required accuracy. In the paper a way of trajectory generation that uses ZMP methodology is discussed, the results of the numerical simulation of the exoskeleton motion are presented and analyzed. A comparison between a natural human motion (for a human not wearing an exoskeleton) and the simulated motion of an exoskeleton using the proposed algorithm is presented.
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Work is supported by RSF, Project № 14-39-00008.
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Jatsun, S., Savin, S., Yatsun, A. (2018). Motion Control Algorithm for a Lower Limb Exoskeleton Based on Iterative LQR and ZMP Method for Trajectory Generation. In: Husty, M., Hofbaur, M. (eds) New Trends in Medical and Service Robots. MESROB 2016. Mechanisms and Machine Science, vol 48. Springer, Cham. https://doi.org/10.1007/978-3-319-59972-4_22
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DOI: https://doi.org/10.1007/978-3-319-59972-4_22
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