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Brenna Argall

Biographic Data

ID9476100
NAMEBrenna Argall
GIVEN NAMESBrenna
FAMILY NAMEArgall
SIGNATUREARGALL B
AFFILIATIONSNorthwestern University
ORCID0000-0002-4280-8492
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2012
LATEST PUBLICATION YEAR2024
H-INDEX0
  • Learning to Control Complex Robots Using High-Dimensional Body-Machine Interfaces

    Open Access•Jong Min Lee, Jongmin Lee et al.•ARTICLE•ACM Transactions on Human-Robot…•2024

    When individuals are paralyzed from injury or damage to the brain, upper body movement and function can be compromised. While the use of body motions to interface with machines has shown to be an effective noninvasive strategy to provide movement assistance and to promote physical rehabilitation, learning to use such interfaces to control complex machines is not well understood. In a five session study, we demonstrate that a subset of an uninjure…

  • Assessing Interaction Dynamics in the Context of Robot Programming by Demonstration

    Open Access•Ana Lucia Pais, Brenna D Argall et al.•ARTICLE•International Journal of Social…•2013

  • Policy Feedback for the Refinement of Learned Motion Control on a Mobile Robot

    Open Access•Brenna D Argall, Brenna Argall et al.•ARTICLE•International Journal of Social…•2012

No prominent works on this page.

  • Policy Feedback for the Refinement of Learned Motion Control on a Mobile Robot

    Open Access•Brenna D Argall, Brenna Argall et al.•ARTICLE•International Journal of Social…•2012

  • Assessing Interaction Dynamics in the Context of Robot Programming by Demonstration

    Open Access•Ana Lucia Pais, Brenna D Argall et al.•ARTICLE•International Journal of Social…•2013

  • Learning to Control Complex Robots Using High-Dimensional Body-Machine Interfaces

    Open Access•Jong Min Lee, Jongmin Lee et al.•ARTICLE•ACM Transactions on Human-Robot…•2024

    When individuals are paralyzed from injury or damage to the brain, upper body movement and function can be compromised. While the use of body motions to interface with machines has shown to be an effective noninvasive strategy to provide movement assistance and to promote physical rehabilitation, learning to use such interfaces to control complex machines is not well understood. In a five session study, we demonstrate that a subset of an uninjure…

Artificial Intelligence (3 works) · Computer Science (3 works) · Engineering (3 works) · Human–computer interaction (3 works) · Robot (3 works) · Human–robot interaction (2 works) · Mobile robot (2 works) · Reinforcement Learning in Robotics (2 works) · Robot Manipulation and Learning (2 works) · Robotics (2 works)

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