Single-Leg Forward Hopping via Nonlinear Modes

Conference Paper (2022)
Author(s)

Davide Calzolari (Deutsches Zentrum für Luft- und Raumfahrt (DLR), Technische Universität München)

C. Della Santina (Technische Universität München, Deutsches Zentrum für Luft- und Raumfahrt (DLR), TU Delft - Learning & Autonomous Control)

Alessandro Massimo Giordano (Technische Universität München, Deutsches Zentrum für Luft- und Raumfahrt (DLR))

Alin Albu-Schaffer (Technische Universität München, Deutsches Zentrum für Luft- und Raumfahrt (DLR))

DOI related publication
https://doi.org/10.23919/ACC53348.2022.9867538 Final published version
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Publication Year
2022
Language
English
Pages (from-to)
506-513
ISBN (print)
978-1-6654-5196-3
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469
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Abstract

Implementing dynamic legged locomotion entails stabilizing oscillatory behaviors in complex mechanical systems. Whenever possible, locomotion algorithms should also exploit the improved capabilities of elastic elements added to the structure to improve efficiency and robustness. This work aims to shed some light on implementing generic dynamic locomotion by stabilizing nonlinear modes. The nonlinear modal analysis extends the linear modal theory to nonlinear systems and thus characterizes the oscillations that a robot can execute as autonomous evolutions. We execute forward hopping motions with a single segmented elastic leg as the first step towards generic modal locomotion. We propose a locomotion algorithm that exploits the modes of an extension of the SLIP model. We develop this strategy to generalize to other robotic systems, and we extensively validate it with experiments on an elastically actuated segmented leg.

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