A major challenge in the design and control of exoskeletons is the preservation of the user.s natural behavior when interacting with these machines. From this point of view, one of the most important features is the transparency of the exoskeleton. An ideally transparent exoskeleton follows the user's movements without interaction forces. This is the goal of many control algorithms proposed in the literature. Traditional algorithms are based on finite state machines and are affected by assistive torque discontinuity problems in the transitions between phases. State-of-the-art methods approach this problem by imposing a smooth transition that does not account for variable walking speed. In this work, the authors propose an innovative control algorithm for a lower-limb exoskeleton. The proposed control aims at solving the torque discontinuity problem, without requiring a smooth transitions strategy. The proposed control algorithm continuously blends the output of two independent single stance dynamic models, by weighting the contribution of each stance model to the total assistance based on the gait phase. A linear regressor is used to produce the weights, and it requires a brief user-specific calibration. Results showed a significant reduction of interaction forces, and a longer stride length when compared to two finite-state-machine-based controls at two speeds on the treadmill and one self-selected-speed in an overground walk.

Gait Phases Blended Control for Enhancing Transparency on Lower-Limb Exoskeletons

Camardella C.;Porcini F.;Filippeschi A.;Marcheschi S.;Solazzi M.;Frisoli A.
2021

Abstract

A major challenge in the design and control of exoskeletons is the preservation of the user.s natural behavior when interacting with these machines. From this point of view, one of the most important features is the transparency of the exoskeleton. An ideally transparent exoskeleton follows the user's movements without interaction forces. This is the goal of many control algorithms proposed in the literature. Traditional algorithms are based on finite state machines and are affected by assistive torque discontinuity problems in the transitions between phases. State-of-the-art methods approach this problem by imposing a smooth transition that does not account for variable walking speed. In this work, the authors propose an innovative control algorithm for a lower-limb exoskeleton. The proposed control aims at solving the torque discontinuity problem, without requiring a smooth transitions strategy. The proposed control algorithm continuously blends the output of two independent single stance dynamic models, by weighting the contribution of each stance model to the total assistance based on the gait phase. A linear regressor is used to produce the weights, and it requires a brief user-specific calibration. Results showed a significant reduction of interaction forces, and a longer stride length when compared to two finite-state-machine-based controls at two speeds on the treadmill and one self-selected-speed in an overground walk.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11382/539831
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