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Design and Validation of a Robotic Knee Exoskeleton with Musculoskeletal Simulation-Derived Biological Torque Control — arXiv:2610.41981

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.41981
License (as archived): CC0-1.0
Archived: 2026-11-02T05:05:50.795Z
SHA-256 of the archived text: 1870adffa80ef498a28a8ab5a535bcbb99a6b0d3fbde077539bfb7b5c4010121
Stable URL of this page: https://metraipolis.com/documento/dc_7ded63a8a6df

How to cite

Design and Validation of a Robotic Knee Exoskeleton with Musculoskeletal Simulation-Derived Biological Torque Control — arXiv:2610.41981 — arXiv (en), https://arxiv.org/abs/2610.41981 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_7ded63a8a6df (Metraipolis archive dc_7ded63a8a6df, sha256 1870adffa80ef498a28a8ab5a535bcbb99a6b0d3fbde077539bfb7b5c4010121)

BibTeX

@misc{dc7ded63a8a6df,
  title = {Design and Validation of a Robotic Knee Exoskeleton with Musculoskeletal Simulation-Derived Biological Torque Control — arXiv:2610.41981},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.41981},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_7ded63a8a6df; sha256 1870adffa80ef498a28a8ab5a535bcbb99a6b0d3fbde077539bfb7b5c4010121},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.41981. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Data-driven controllers have enabled lower-limb robotic exoskeletons to adapt assistance to the user across many tasks. A leading example is biological torque control, which estimates the user's own joint moment from onboard sensors and assists in proportion to that estimate. However, its estimators are trained on data recorded with the target device, so deploying the controller on new hardware requires collecting new data. Existing open-source efforts release hardware, software, or controllers separately, so this data collection must still be repeated on the assembled device. Here, we present an open-source knee exoskeleton, built from off-the-shelf components and widely available fabrication tools, with a biological torque controller derived entirely from simulation. A muscle-driven imitation policy reproduces squatting motions from an open biomechanics dataset, and the resulting knee moments are distilled into an estimator that uses only onboard sensors, so no training data are recorded on the device. In seven able-bodied participants, assistance reduced peak biological knee extension moment by 21.5% and peak vastus medialis activation by 26.7% during squatting, relative to squatting without the exoskeleton (p<0.05). Our results demonstrate that a biological torque controller derived from simulation can transfer to physical hardware without device-specific data collection. Because the hardware and training pipeline are released together, research groups can train and compare knee exoskeleton controllers on shared hardware without additional data collection overhead.

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv cs.RO, nuovi lavori del giorno).
Categorie arXiv: Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2610.41981 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-02T04:49:28.235Z dalla pagina https://arxiv.org/list/cs.RO/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).