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Robustness and efficiency insights from a mechanical coupling metric for ankle-actuated biped robots

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Abstract

This paper presents results pertaining to the coupling between the actuated and unactuated degrees of freedom for biped robots. It is focused on revealing the qualitative relationship between a mechanical coupling metric and gait characteristics for an ankle-actuated biped robot. By considering robot models with varying masses, leg lengths and positions of the center of mass of the legs, it validates the universality of prior results based on a single robot model. The development of a method for designing ankle-actuated biped gaits is given in detail, and numerical computation is utilized to find the initial conditions needed to generate the ankle-actuated candidate gait regions. The correlation between the coupling metric and the maximum magnitude of disturbance that can be rejected is significant, regardless of the robot parameters. It indicates that robust gaits tend to have small coupling under zero disturbance so that the “reserve” coupling may be utilized to reject the disturbance. Furthermore, for the same walking speed, gaits with smaller cost of transport under zero disturbances have smaller coupling and therefore should be more robust, which highlights the value of gait optimization for biped walking. The coupling metric for hip actuation is also briefly discussed as a contrast.

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Notes

  1. The cost of transport quantifies the energy efficiency of walking.

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Acknowledgements

The partial support of the US National Science Foundation under Grant IIS-1527393 is gratefully acknowledged.

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Authors and Affiliations

  1. Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA

    Tan Chen, James P. Schmiedeler & Bill Goodwine

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  1. Tan Chen
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  2. James P. Schmiedeler
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  3. Bill Goodwine
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Correspondence to Tan Chen.

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Chen, T., Schmiedeler, J.P. & Goodwine, B. Robustness and efficiency insights from a mechanical coupling metric for ankle-actuated biped robots. Auton Robot 44, 281–295 (2020). https://doi.org/10.1007/s10514-019-09893-w

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