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Grip Stabilization through Independent Finger Tactile Feedback Control

Veiga, Filipe ; Edin, Benoni ; Peters, Jan (2024)
Grip Stabilization through Independent Finger Tactile Feedback Control.
In: Sensors, 2020, 20 (6)
doi: 10.26083/tuprints-00016296
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Grip Stabilization through Independent Finger Tactile Feedback Control
Language: English
Date: 16 January 2024
Place of Publication: Darmstadt
Year of primary publication: 2020
Place of primary publication: Basel
Publisher: MDPI
Journal or Publication Title: Sensors
Volume of the journal: 20
Issue Number: 6
Collation: 17 Seiten
DOI: 10.26083/tuprints-00016296
Corresponding Links:
Origin: Secondary publication DeepGreen
Abstract:

Grip force control during robotic in-hand manipulation is usually modeled as a monolithic task, where complex controllers consider the placement of all fingers and the contact states between each finger and the gripped object in order to compute the necessary forces to be applied by each finger. Such approaches normally rely on object and contact models and do not generalize well to novel manipulation tasks. Here, we propose a modular grip stabilization method based on a proposition that explains how humans achieve grasp stability. In this biomimetic approach, independent tactile grip stabilization controllers ensure that slip does not occur locally at the engaged robot fingers. Local slip is predicted from the tactile signals of each fingertip sensor i.e., BioTac and BioTac SP by Syntouch. We show that stable grasps emerge without any form of central communication when such independent controllers are engaged in the control of multi-digit robotic hands. The resulting grasps are resistant to external perturbations while ensuring stable grips on a wide variety of objects.

Uncontrolled Keywords: in-hand manipulation, modular control, reactive control, tactile feedback, independent finger control, slip prediction
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-162966
Additional Information:

This article belongs to the Special Issue Sensors and Robot Control

Classification DDC: 000 Generalities, computers, information > 004 Computer science
600 Technology, medicine, applied sciences > 610 Medicine and health
Divisions: 20 Department of Computer Science > Intelligent Autonomous Systems
Date Deposited: 16 Jan 2024 10:51
Last Modified: 02 Apr 2024 12:27
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/16296
PPN: 516712241
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