Out-of-sight partners: autonomous wearable supernumerary limbs for dynamic co-manipulation
- 1Imperial College of Science Technology and Medicine: Imperial College London
Abstract
Supernumerary robotic limbs (SLs) could extend human motor capabilities beyond the natural body, yet most demonstrations have been limited to simple, quasi-static tasks or direct teleoperation under visual control. Whether humans can safely and intuitively collaborate with autonomous SLs during complex, dynamic tasks remains unknown. We studied this question in a demanding assembly task requiring coordinated transport and handovers of a long object, which could not be completed by a single person. We developed a reconfigurable backpack platform mounting up to four high-payload robotic arms, together with safety-aware motion planning that generates human-compatible trajectories from task states without training data. Despite the SLs operating out of sight, participants adapted quickly, completed the task reliably, and reported low cognitive demand alongside high perceived safety and predictability. Kinematic and force analyses showed that control design governed both movement fluency and whole-body stability: faster limb motions yielded smoother interactions and shorter completion times, and a mirrored coordination strategy--in which one robotic limb counterbalanced the other--further shortened duration and reduced variability in left-right ground reaction force differences during co-manipulation. These results show that humans can integrate autonomous wearable limbs as out-of-sight partners in dynamic whole-body collaboration, and delineate behavioral and control principles underpinning fluency, stability, and usability in human augmentation.
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BibTeX
@misc{verdel2026outofsight,
title = {{Out-of-sight partners: autonomous wearable supernumerary limbs for dynamic co-manipulation}},
author = {D. Verdel and B. Xu and H. Cervantes-Culebro and A. Devillard and L. Mattioli and D. Farina and P. Soueres and E. Burdet},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.02.748789},
url = {https://www.biorxiv.org/content/10.64898/2026.09.02.748789v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Out-of-sight partners: autonomous wearable supernumerary limbs for dynamic co-manipulation
AU - D. Verdel
AU - B. Xu
AU - H. Cervantes-Culebro
AU - A. Devillard
AU - L. Mattioli
AU - D. Farina
AU - P. Soueres
AU - E. Burdet
PY - 2026
DA - 2026/09/02
PB - bioRxiv
DO - 10.64898/2026.09.02.748789
UR - https://www.biorxiv.org/content/10.64898/2026.09.02.748789v1
AB - Supernumerary robotic limbs (SLs) could extend human motor capabilities beyond the natural body, yet most demonstrations have been limited to simple, quasi-static tasks or direct teleoperation under visual control. Whether humans can safely and intuitively collaborate with autonomous SLs during complex, dynamic tasks remains unknown. We studied this question in a demanding assembly task requiring coordinated transport and handovers of a long object, which could not be completed by a single person. We developed a reconfigurable backpack platform mounting up to four high-payload robotic arms, together with safety-aware motion planning that generates human-compatible trajectories from task states without training data. Despite the SLs operating out of sight, participants adapted quickly, completed the task reliably, and reported low cognitive demand alongside high perceived safety and predictability. Kinematic and force analyses showed that control design governed both movement fluency and whole-body stability: faster limb motions yielded smoother interactions and shorter completion times, and a mirrored coordination strategy--in which one robotic limb counterbalanced the other--further shortened duration and reduced variability in left-right ground reaction force differences during co-manipulation. These results show that humans can integrate autonomous wearable limbs as out-of-sight partners in dynamic whole-body collaboration, and delineate behavioral and control principles underpinning fluency, stability, and usability in human augmentation.
ER -