Electrohydraulic musculoskeletal robotic leg for agile, adaptive, yet energy-efficient locomotion

Robotic locomotion in unstructured terrain demands an agile, adaptive, and energy-efficient architecture. To traverse such terrains, legged robots use rigid electromagnetic motors and sensorized drivetrains to adapt to the environment actively. These systems struggle to compete with animals that excel through their agile and effortless motion in natural environments. We propose a bio-inspired musculoskeletal leg architecture driven by antagonistic pairs of electrohydraulic artificial muscles. Our leg is mounted on a boom arm and can adaptively hop on varying terrain in an energy-efficient yet agile manner. It can also detect obstacles through capacitive self-sensing. The leg performs powerful and agile gait motions beyond 5 Hz and high jumps up to 40 % of the leg height. Our leg's tunable stiffness and inherent adaptability allow it to hop over grass, sand, gravel, pebbles, and large rocks using only open-loop force control. The electrohydraulic leg features a low cost of transport (0.73), and while squatting, it consumes only a fraction of the energy (1.2 %) compared to its conventional electromagnetic counterpart. Its agile, adaptive, and energy-efficient properties would open a roadmap toward a new class of musculoskeletal robots for versatile locomotion and operation in unstructured natural environments.

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Publication Details

Journal
Nature Communications
Published
2024-09-09
DOI
https://doi.org/10.1038/s41467-024-51568-3
Citations
51
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
9.41

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article

Electrohydraulic musculoskeletal robotic leg for agile, adaptive, yet energy-efficient locomotion

Christoph Keplinger, Toshihiko Fukushima, Johannes Walter, Stephan-Daniel Gravert et al.
51 citations
Nature Communications
Soft Robotics and Applications
9.41
article

Electrohydraulic musculoskeletal robotic leg for agile, adaptive, yet energy-efficient locomotion

Christoph Keplinger, Toshihiko Fukushima, Johannes Walter, Stephan-Daniel Gravert, Amirhossein Kazemipour, Philip Arm, Robert K. Katzschmann, Xingrui Wang, Thomas Büchner, Yu Zhang, Steven Zhang, Manon Prairie, Pascal Romanescu
article en
51 citations

Abstract

Robotic locomotion in unstructured terrain demands an agile, adaptive, and energy-efficient architecture. To traverse such terrains, legged robots use rigid electromagnetic motors and sensorized drivetrains to adapt to the environment actively. These systems struggle to compete with animals that excel through their agile and effortless motion in natural environments. We propose a bio-inspired musculoskeletal leg architecture driven by antagonistic pairs of electrohydraulic artificial muscles. Our leg is mounted on a boom arm and can adaptively hop on varying terrain in an energy-efficient yet agile manner. It can also detect obstacles through capacitive self-sensing. The leg performs powerful and agile gait motions beyond 5 Hz and high jumps up to 40 % of the leg height. Our leg's tunable stiffness and inherent adaptability allow it to hop over grass, sand, gravel, pebbles, and large rocks using only open-loop force control. The electrohydraulic leg features a low cost of transport (0.73), and while squatting, it consumes only a fraction of the energy (1.2 %) compared to its conventional electromagnetic counterpart. Its agile, adaptive, and energy-efficient properties would open a roadmap toward a new class of musculoskeletal robots for versatile locomotion and operation in unstructured natural environments.

Nature CommunicationsVol. 15(1)
University of Colorado Boulder (US), ETH Zurich (CH), Max Planck Institute for Intelligent Systems (DE)
National Science Foundation, International Max Planck Research School for Environmental, Cellular and Molecular Microbiology, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Eidgenössische Technische Hochschule Zürich, Max-Planck-Gesellschaft, National Centre of Competence in Research Robotics, International Max Planck Research School for Advanced Methods in Process and Systems Engineering
Affordable and clean energy
Openalex Percentile: Top 1%
Soft Robotics and Applications
9.41
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