Human-Robot Interaction through an Object Grasped with Two Fingers Based on Plastic Deformation Control

In this study, two-finger grasping based on plastic deformation control for human-robot interaction is designed and implemented. This control strategy is derived based on the concept that balances both retention of grasping force on objects and plastic behavior in response to external forces. The control law consists of a set of constraints and offsets with respect to the springs that appear in the Maxwell model. In particular, the inner loop that is robust against parameter errors is implemented for actual machine experiments. Simulation and actual experiments with a robotic hand are executed to validate the proposed control law.

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Publication Details

Published
2024-12-10
DOI
https://doi.org/10.1109/robio64047.2024.10907693
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Human-Robot Interaction through an Object Grasped with Two Fingers Based on Plastic Deformation Control

Taku Senoo, Idaku Ishii, Hiromichi Kawahara, Atsushi Konno
Robot Manipulation and Learning
article

Human-Robot Interaction through an Object Grasped with Two Fingers Based on Plastic Deformation Control

Taku Senoo, Idaku Ishii, Hiromichi Kawahara, Atsushi Konno
article en

Abstract

In this study, two-finger grasping based on plastic deformation control for human-robot interaction is designed and implemented. This control strategy is derived based on the concept that balances both retention of grasping force on objects and plastic behavior in response to external forces. The control law consists of a set of constraints and offsets with respect to the springs that appear in the Maxwell model. In particular, the inner loop that is robust against parameter errors is implemented for actual machine experiments. Simulation and actual experiments with a robotic hand are executed to validate the proposed control law.

Hiroshima University (JP), Hokkaido University (JP)
Openalex Percentile: Top 65%
Robot Manipulation and Learning
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