Efficient and Goal-Directed Oscillations in Articulated Soft Robots

Bonacchi, Luigi Bono Bonacchi; Roa, Maximo A.; Sesselmann, Anna; Loeffl, Florian; Albu-Schaffer, Alin; Della Santina, C.

doi:10.1109/LRA.2021.3061345

Efficient and Goal-Directed Oscillations in Articulated Soft Robots

the Point-to-Point Case

Journal article (2021)

Authors

Luigi Bono Bonacchi Bonacchi Deutsches Zentrum für Luft- und Raumfahrt (DLR)

Maximo A. Roa Deutsches Zentrum für Luft- und Raumfahrt (DLR)

Anna Sesselmann Deutsches Zentrum für Luft- und Raumfahrt (DLR)

Florian Loeffl Deutsches Zentrum für Luft- und Raumfahrt (DLR)

Alin Albu-Schaffer Deutsches Zentrum für Luft- und Raumfahrt (DLR)

C. Della Santina Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering

Research Group

Learning & Autonomous Control (Mechanical, Maritime and Materials Engineering) (TU Delft)

DOI: https://doi.org/10.1109/LRA.2021.3061345

Robots Oscillators Mathematical model Motion Control Damping Soft robotics Task analysis Robot kinematics Compliant Joints and Mechanisms Natural Machine Motion

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Published Date

2021

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Learning & Autonomous Control

Abstract

Introducing elasticity in the mechanical design can endow robots with the ability of performing efficient and effective periodic motions. Yet, devising controllers that can take advantage of such elasticity is still an open challenge. This letter tackles an instance of this general problem, by proposing a control architecture for executing goal-oriented and efficient point-to-point periodic motions. This is achieved by (i) producing motor torques that excite intrinsic modal oscillations, and simultaneously (ii) adjusting parallel elasticity so to shape the natural modes. Analytical proofs of convergence are provided for the linear approximation. The performance and efficiency (in the sense of low energy expenditure) of the method in the nonlinear case are assessed with extensive simulations and experiments.

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