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Model Predictive Control-based gait pattern generation for wearable exoskeletons.

Letian Wang1, Edwin H F van Asseldonk, Herman van der Kooij

  • 1Laboratory of Biomechanical Engineering, University of Twente, 7500 EA Enschede, The Netherlands. letian.wang@utwente.nl

IEEE ... International Conference on Rehabilitation Robotics : [Proceedings]
|January 26, 2012
PubMed
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This study presents a new exoskeleton control method using gait descriptors instead of joint trajectories. It enables real-time control for diverse walking patterns, enhancing exoskeleton assistance.

Area of Science:

  • Robotics
  • Biomechanics
  • Human-Computer Interaction

Background:

  • Wearable exoskeletons require sophisticated control systems for effective human assistance.
  • Current methods often rely on predefined joint trajectories, limiting adaptability.
  • A need exists for intuitive control adaptable to natural human gait variations.

Purpose of the Study:

  • To introduce and evaluate a novel control method for wearable exoskeletons.
  • To demonstrate control based on basic gait descriptors rather than fixed trajectories.
  • To assess the real-time performance and adaptability of the proposed control strategy.

Main Methods:

  • Utilizing End-point Model Predictive Control (MPC) for online joint trajectory generation.
  • Employing basic gait descriptors: step length, swing duration, and walking speed.

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  • Conducting experiments on the LOPES gait trainer with human subjects.

    • Main Results:

    • The method successfully generated adaptable joint trajectories without predefined paths.
    • Demonstrated real-time control capabilities during the swing phase of the gait cycle.
    • Experimental results confirmed the system's ability to assist varied step patterns and durations.

    Conclusions:

    • The proposed gait descriptor-based MPC method offers a flexible and effective approach to exoskeleton control.
    • The system is computationally efficient, suitable for real-time applications.
    • Future work will extend this control strategy to the entire gait cycle.