Bootstrapping the Dynamic Gait Controller of the Soft Robot Arm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00367804" target="_blank" >RIV/68407700:21230/23:00367804 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/ICRA48891.2023.10160579" target="_blank" >https://doi.org/10.1109/ICRA48891.2023.10160579</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICRA48891.2023.10160579" target="_blank" >10.1109/ICRA48891.2023.10160579</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Bootstrapping the Dynamic Gait Controller of the Soft Robot Arm

Popis výsledku v původním jazyce

In this paper, we propose a novel dynamic gait controller for the repetitive behavior of soft robot manipulators performing routine tasks. Compliance with soft robots is advantageous when the robot interacts with living organisms and other fragile objects. However, predicting and controlling repetitive behavior is challenging because of hysteresis and non-linear dynamics governing the interactions. Existing priorfree methods track the dynamic state using recurrent neural networks or rely on known generalized coordinates describing the robot's state. We propose to model the interaction induced by the repetitive behavior as gait dynamics and represent the dynamic state with Central Pattern Generator (CPG) tracking the motion phase and thus reduce the complexity of the robot's forward model. The proposed method bootstraps an ensemble of the forward models exploring multiple dynamic contexts that are expanded as it searches for repetitive motion producing the target repetitive behavior. The proposed approach is experimentally validated on a pneumatically actuated soft robot arm I-Support, where the method infers gaits for different targets.

Název v anglickém jazyce

Bootstrapping the Dynamic Gait Controller of the Soft Robot Arm

Popis výsledku anglicky

In this paper, we propose a novel dynamic gait controller for the repetitive behavior of soft robot manipulators performing routine tasks. Compliance with soft robots is advantageous when the robot interacts with living organisms and other fragile objects. However, predicting and controlling repetitive behavior is challenging because of hysteresis and non-linear dynamics governing the interactions. Existing priorfree methods track the dynamic state using recurrent neural networks or rely on known generalized coordinates describing the robot's state. We propose to model the interaction induced by the repetitive behavior as gait dynamics and represent the dynamic state with Central Pattern Generator (CPG) tracking the motion phase and thus reduce the complexity of the robot's forward model. The proposed method bootstraps an ensemble of the forward models exploring multiple dynamic contexts that are expanded as it searches for repetitive motion producing the target repetitive behavior. The proposed approach is experimentally validated on a pneumatically actuated soft robot arm I-Support, where the method infers gaits for different targets.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

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

2023

Kód důvěrnosti údajů

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

Název statě ve sborníku

2023 IEEE International Conference on Robotics and Automation

ISBN

979-8-3503-2365-8

ISSN

1050-4729

e-ISSN

2577-087X

Počet stran výsledku

7

Strana od-do

2669-2675

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Londýn

Datum konání akce

29. 5. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001036713002010