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- Title
Electrohydraulic musculoskeletal robotic leg for agile, adaptive, yet energy-efficient locomotion.
- Authors
Buchner, Thomas J. K.; Fukushima, Toshihiko; Kazemipour, Amirhossein; Gravert, Stephan-Daniel; Prairie, Manon; Romanescu, Pascal; Arm, Philip; Zhang, Yu; Wang, Xingrui; Zhang, Steven L.; Walter, Johannes; Keplinger, Christoph; Katzschmann, Robert K.
- 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. Future bioinspired locomotion systems need design's agility and adaptiveness. Here, the authors report a musculoskeletal leg design which leverages multi-layered electrohydraulic actuators to achieve highly energy-efficient and versatile motion.
- Subjects
ARTIFICIAL muscles; PEBBLES; GRAVEL; TRANSPORTATION costs; ACTUATORS; BIOLOGICALLY inspired computing
- Publication
Nature Communications, 2024, Vol 15, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-024-51568-3