Dynamic Primitives Limit Human Force Regulation during Motion
| Autor: | A. Michael West, James Hermus, Meghan E. Huber, Pauline Maurice, Dagmar Sternad, Neville Hogan |
|---|---|
| Přispěvatelé: | Department of Mechanical Engineering [Massachusetts Institute of Technology] (MIT-MECHE), Massachusetts Institute of Technology (MIT), University of Massachusetts [Amherst] (UMass Amherst), University of Massachusetts System (UMASS), Lifelong Autonomy and interaction skills for Robots in a Sensing ENvironment (LARSEN), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Department of Biology, Northeastern University, Northeastern University [Boston] |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Compliance and Impedance Control
Human-Computer Interaction Control and Optimization Force Control Artificial Intelligence Control and Systems Engineering Mechanical Engineering Physical Human-Robot Interaction Biomedical Engineering [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO] Computer Vision and Pattern Recognition Article Computer Science Applications |
| Zdroj: | IEEE Robot Autom Lett IEEE Robotics and Automation Letters IEEE Robotics and Automation Letters, 2022, 7 (2), pp.2391-2398. ⟨10.1109/LRA.2022.3141778⟩ |
| ISSN: | 2377-3766 |
| DOI: | 10.1109/LRA.2022.3141778⟩ |
| Popis: | International audience; Humans excel at physical interaction despite long feedback delays and low-bandwidth actuators. Yet little is known about how humans manage physical interaction. A quantitative understanding of how they do is critical for designing machines that can safely and effectively interact with humans, e.g. amputation prostheses, assistive exoskeletons, therapeutic rehabilitation robots, and physical human-robot collaboration. To facilitate applications, this understanding should be in the form of a simple mathematical model that not only describes humans' capabilities but also their limitations. In robotics, hybrid control allows simultaneous, independent control of both motion and force and it is often assumed that humans can modulate force independent of motion as well. This paper experimentally tested that assumption. Participants were asked to apply a constant 5N force on a robot manipulandum that moved along an elliptical path. After initial improvement, force errors quickly plateaued, despite practice and visual feedback. Within-trial analyses revealed that force errors varied with position on the ellipse, rejecting the hypothesis that humans have independent control of force and motion. The findings are consistent with a feed-forward motion command composed of two primitive oscillations acting through mechanical impedance to evoke force. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|