On Robot Compliance: A Cerebellar Control Approach.


Journal

IEEE transactions on cybernetics
ISSN: 2168-2275
Titre abrégé: IEEE Trans Cybern
Pays: United States
ID NLM: 101609393

Informations de publication

Date de publication:
May 2021
Historique:
pubmed: 28 10 2019
medline: 19 8 2021
entrez: 25 10 2019
Statut: ppublish

Résumé

The work presented here is a novel biological approach for the compliant control of a robotic arm in real time (RT). We integrate a spiking cerebellar network at the core of a feedback control loop performing torque-driven control. The spiking cerebellar controller provides torque commands allowing for accurate and coordinated arm movements. To compute these output motor commands, the spiking cerebellar controller receives the robot's sensorial signals, the robot's goal behavior, and an instructive signal. These input signals are translated into a set of evolving spiking patterns representing univocally a specific system state at every point of time. Spike-timing-dependent plasticity (STDP) is then supported, allowing for building adaptive control. The spiking cerebellar controller continuously adapts the torque commands provided to the robot from experience as STDP is deployed. Adaptive torque commands, in turn, help the spiking cerebellar controller to cope with built-in elastic elements within the robot's actuators mimicking human muscles (inherently elastic). We propose a natural integration of a bioinspired control scheme, based on the cerebellum, with a compliant robot. We prove that our compliant approach outperforms the accuracy of the default factory-installed position control in a set of tasks used for addressing cerebellar motor behavior: controlling six degrees of freedom (DoF) in smooth movements, fast ballistic movements, and unstructured scenario compliant movements.

Identifiants

pubmed: 31647453
doi: 10.1109/TCYB.2019.2945498
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2476-2489

Auteurs

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Classifications MeSH