Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloAssisting Operators in Heavy Industrial Tasks: On the Design of an Optimized Cooperative Impedance Fuzzy-Controller With Embedded Safety Rules
Anno di pubblicazione2019
Autore/iRoveda, Loris; Haghshenas, Shaghayegh; Caimmi, Marco; Pedrocchi, Nicola; Tosatti, Lorenzo Molinari
Affiliazioni autoriUniv. Svizzera Italiana; CNR; CNR; CNR; CNR;
Autori CNR e affiliazioni
  • inglese
AbstractHuman-robot cooperation is increasingly demanded in industrial applications. Many tasks require the robot to enhance the capabilities of humans. In this scenario, safety also plays an important role in avoiding any accident involving humans, robots, and the environment. With this aim, the paper proposes a cooperative fuzzy-impedance control with embedded safety rules to assist human operators in heavy industrial applications while manipulating unknown weight parts. The proposed methodology is composed by four main components: (i) an inner Cartesian impedance controller (to achieve the compliant robot behavior), (ii) an outer fuzzy controller (to provide the assistance to the human operator), (iii) embedded safety rules (to limit force/velocity during the human-robot interaction enhancing safety), and (iv) a neural network approach (to optimize the control parameters for the human-robot collaboration on the basis of the target indexes of assistance performance defined for this purpose). The main achieved result refers to the capability of the controller to deal with uncertain payloads while assisting and empowering the human operator, both embedding in the controller safety features at force and velocity levels and minimizing the proposed performance indexes. The effectiveness of the proposed approach is verified with a KUKA iiwa 14 R820 manipulator in an experimental procedure where human subjects evaluate the robot performance in a collaborative lifting task of a 10 kg part.
Lingua abstractinglese
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Pagine da-
Pagine a-
Pagine totali19
RivistaFrontiers in Robotics and AI
Attiva dal 2014
Editore: Mel Slater - Barcellona/Spagna
Paese di pubblicazione: Svizzera
Lingua: inglese
ISSN: 2296-9144
Titolo chiave: Frontiers in Robotics and AI
Numero volume della rivista6
Fascicolo della rivista-
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000482081000002)
  • Scopus (Codice:2-s2.0-85080959554)
Parole chiavehuman-robot cooperation, neural network human-robot interaction mapping, machine learning for autonomous control tuning, fuzzy logic safe controller, empowering humans, human-robot collaboration evaluation, variable impedance control
Link (URL, URI)
Titolo parallelo-
LicenzaCC BY
Scadenza embargo-
Data di accettazione02/08/2019
Note/Altre informazioni-
Strutture CNR
  • STIIMA — Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato
Moduli/Attività/Sottoprogetti CNR
  • DIT.AD008.064.001 : EURECA Development of system components for automated cabin and cargo installation
  • DIT.AD008.125.001 : StepbyStep - Sistematic Test of Exoskeleton
Progetti Europei