Single-Grasp Deformable Object Discrimination: The Effect of Gripper Morphology, Sensing Modalities, and Action Parameters

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F24%3A00378042" target="_blank" >RIV/68407700:21730/24:00378042 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/24:00378042

Výsledek na webu

<a href="https://doi.org/10.1109/TRO.2024.3463402" target="_blank" >https://doi.org/10.1109/TRO.2024.3463402</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TRO.2024.3463402" target="_blank" >10.1109/TRO.2024.3463402</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Single-Grasp Deformable Object Discrimination: The Effect of Gripper Morphology, Sensing Modalities, and Action Parameters

Popis výsledku v původním jazyce

In haptic object discrimination, the effect of gripper embodiment, action parameters, and sensory channels has not been systematically studied. We used two anthropomorphic hands and two 2-finger grippers to grasp two sets of deformable objects. On the object classification task, we found: (i) among classifiers, SVM on sensory features and LSTM on raw time series performed best across all grippers; (ii) faster compression speeds degraded performance; (iii) generalization to different grasping configurations was limited; transfer to different compression speeds worked well for the Barrett Hand only. Visualization of the feature spaces using PCA showed that gripper morphology and action parameters were the main source of variance, making generalization across embodiment or grip configurations very difficult. On the highly challenging dataset consisting of polyurethane foams alone, only the Barrett Hand achieved excellent performance. Tactile sensors can thus provide a key advantage even if recognition is based on stiffness rather than shape. The data set with 24,000 measurements is publicly available.

Název v anglickém jazyce

Single-Grasp Deformable Object Discrimination: The Effect of Gripper Morphology, Sensing Modalities, and Action Parameters

Popis výsledku anglicky

In haptic object discrimination, the effect of gripper embodiment, action parameters, and sensory channels has not been systematically studied. We used two anthropomorphic hands and two 2-finger grippers to grasp two sets of deformable objects. On the object classification task, we found: (i) among classifiers, SVM on sensory features and LSTM on raw time series performed best across all grippers; (ii) faster compression speeds degraded performance; (iii) generalization to different grasping configurations was limited; transfer to different compression speeds worked well for the Barrett Hand only. Visualization of the feature spaces using PCA showed that gripper morphology and action parameters were the main source of variance, making generalization across embodiment or grip configurations very difficult. On the highly challenging dataset consisting of polyurethane foams alone, only the Barrett Hand achieved excellent performance. Tactile sensors can thus provide a key advantage even if recognition is based on stiffness rather than shape. The data set with 24,000 measurements is publicly available.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Transactions on Robotics

ISSN

1552-3098

e-ISSN

1941-0468

Svazek periodika

40

Číslo periodika v rámci svazku

9

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

4414-4426

Kód UT WoS článku

001336003000001

EID výsledku v databázi Scopus

2-s2.0-85204440808