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Main Authors: Honji, Sumitaka, Arita, Hikaru, Tahara, Kenji
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2306.07035
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author Honji, Sumitaka
Arita, Hikaru
Tahara, Kenji
author_facet Honji, Sumitaka
Arita, Hikaru
Tahara, Kenji
contents Soft robots have high adaptability and safeness which are derived from their softness, and therefore it is paid attention to use them in human society. However, the controllability of soft robots is not enough to perform dexterous behaviors when considering soft robots as alternative laborers for humans. The model-based control is effective to achieve dexterous behaviors. When considering building a model which is suitable for control, there are problems based on their special properties such as the creep behavior or the variability of motion. In this paper, the lumped parameterized model with viscoelastic joints for a soft finger is established for the creep behavior. Parameters are expressed as distributions, which makes it possible to take into account the variability of motion. Furthermore, stochastic analyses are performed based on the parameters' distribution. They show high adaptivity compared with experimental results and also enable the investigation of the effects of parameters for robots' variability.
format Preprint
id arxiv_https___arxiv_org_abs_2306_07035
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Stochastic Approach for Modeling a Soft Robotic Finger with Creep Behavior
Honji, Sumitaka
Arita, Hikaru
Tahara, Kenji
Robotics
Soft robots have high adaptability and safeness which are derived from their softness, and therefore it is paid attention to use them in human society. However, the controllability of soft robots is not enough to perform dexterous behaviors when considering soft robots as alternative laborers for humans. The model-based control is effective to achieve dexterous behaviors. When considering building a model which is suitable for control, there are problems based on their special properties such as the creep behavior or the variability of motion. In this paper, the lumped parameterized model with viscoelastic joints for a soft finger is established for the creep behavior. Parameters are expressed as distributions, which makes it possible to take into account the variability of motion. Furthermore, stochastic analyses are performed based on the parameters' distribution. They show high adaptivity compared with experimental results and also enable the investigation of the effects of parameters for robots' variability.
title Stochastic Approach for Modeling a Soft Robotic Finger with Creep Behavior
topic Robotics
url https://arxiv.org/abs/2306.07035