Zobraziť v EDS

Model-Based Predictive Impedance Variation for Obstacle Avoidance in Safe Human–Robot Collaboration

Uložené v:
Podrobná bibliografia
Názov: Model-Based Predictive Impedance Variation for Obstacle Avoidance in Safe Human–Robot Collaboration
Autori: Salt Ducaju, Julian, Olofsson, Björn, Johansson, Rolf
Prispievatelia: Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Engineering Health, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Teknik för hälsa, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Automatic Control, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för reglerteknik, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator
Zdroj: IEEE Transactions on Automation Science and Engineering. 22:9571-9583
Predmety: Engineering and Technology, Electrical Engineering, Electronic Engineering, Information Engineering, Control Engineering, Teknik, Elektroteknik och elektronik, Reglerteknik, Robotics and automation, Robotik och automation
Popis: Human–robot collaboration (HRC) in manufacturing environments requires that physical safety can be guaranteed. Control methods that implicitly regulate the interaction forces between a controlled robot and its environment, such as impedance control, are often used for safety in HRC. However, these methods could be complemented by restricting the robot operational space for additional safety guarantees. In this context, obstacle avoidance might benefit from considering a prediction of the controlled-robot motion and/or the behavior of the human collaborator. To this end, we proposed to include linearized Safety Control Barrier Functions (SCBFs) in a linear Model Predictive Control (MPC) strategy for robot impedance variation online. The convex optimization problem that was obtained from our proposal presented two advantages compared to nonlinear MPC alternatives. First, optimality was ensured in our method under linearity assumptions on human guidance and linearized robot dynamics, whereas a controller synthesized by nonlinear MPC strategies would depend on the fundamental characteristics of the problem. Second, our method enabled implementation at a faster control frequency, thus allowing a rapid adaptation to changes occurring in the robot environment. Finally, experimental validation was performed using a Franka Emika Panda robot in a human–robot collaborative scenario, and the stability of the method was shown using Lyapunov theory.
Popis súboru: electronic
Prístupová URL adresa: https://lucris.lub.lu.se/ws/files/206302831/TASE_FINAL.pdf
Databáza: SwePub
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://lucris.lub.lu.se/ws/files/206302831/TASE_FINAL.pdf#
    Name: EDS - SwePub (s4221598)
    Category: fullText
    Text: View record in SwePub
  – Url: https://resolver.ebscohost.com/openurl?sid=EBSCO:edsswe&genre=article&issn=15455955&ISBN=&volume=22&issue=&date=20250101&spage=9571&pages=9571-9583&title=IEEE Transactions on Automation Science and Engineering&atitle=Model-Based%20Predictive%20Impedance%20Variation%20for%20Obstacle%20Avoidance%20in%20Safe%20Human%E2%80%93Robot%20Collaboration&aulast=Salt%20Ducaju%2C%20Julian&id=DOI:10.1109/TASE.2024.3508718
    Name: Full Text Finder
    Category: fullText
    Text: Full Text Finder
    Icon: https://imageserver.ebscohost.com/branding/images/FTF.gif
    MouseOverText: Full Text Finder
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Ducaju%20S
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: edsswe
DbLabel: SwePub
An: edsswe.oai.portal.research.lu.se.publications.e953e5f3.42c4.49f3.a6dd.39e7b844d42d
RelevancyScore: 1115
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 1114.736328125
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Model-Based Predictive Impedance Variation for Obstacle Avoidance in Safe Human–Robot Collaboration
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Salt+Ducaju%2C+Julian%22">Salt Ducaju, Julian</searchLink><br /><searchLink fieldCode="AR" term="%22Olofsson%2C+Björn%22">Olofsson, Björn</searchLink><br /><searchLink fieldCode="AR" term="%22Johansson%2C+Rolf%22">Johansson, Rolf</searchLink>
– Name: Author
  Label: Contributors
  Group: Au
  Data: Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Engineering Health, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Teknik för hälsa, Originator<br />Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator<br />Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Automatic Control, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för reglerteknik, Originator<br />Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator<br />Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <i>IEEE Transactions on Automation Science and Engineering</i>. 22:9571-9583
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Engineering+and+Technology%22">Engineering and Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Electrical+Engineering%22">Electrical Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Engineering%22">Electronic Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Engineering%22">Information Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Control+Engineering%22">Control Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Teknik%22">Teknik</searchLink><br /><searchLink fieldCode="DE" term="%22Elektroteknik+och+elektronik%22">Elektroteknik och elektronik</searchLink><br /><searchLink fieldCode="DE" term="%22Reglerteknik%22">Reglerteknik</searchLink><br /><searchLink fieldCode="DE" term="%22Robotics+and+automation%22">Robotics and automation</searchLink><br /><searchLink fieldCode="DE" term="%22Robotik+och+automation%22">Robotik och automation</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Human–robot collaboration (HRC) in manufacturing environments requires that physical safety can be guaranteed. Control methods that implicitly regulate the interaction forces between a controlled robot and its environment, such as impedance control, are often used for safety in HRC. However, these methods could be complemented by restricting the robot operational space for additional safety guarantees. In this context, obstacle avoidance might benefit from considering a prediction of the controlled-robot motion and/or the behavior of the human collaborator. To this end, we proposed to include linearized Safety Control Barrier Functions (SCBFs) in a linear Model Predictive Control (MPC) strategy for robot impedance variation online. The convex optimization problem that was obtained from our proposal presented two advantages compared to nonlinear MPC alternatives. First, optimality was ensured in our method under linearity assumptions on human guidance and linearized robot dynamics, whereas a controller synthesized by nonlinear MPC strategies would depend on the fundamental characteristics of the problem. Second, our method enabled implementation at a faster control frequency, thus allowing a rapid adaptation to changes occurring in the robot environment. Finally, experimental validation was performed using a Franka Emika Panda robot in a human–robot collaborative scenario, and the stability of the method was shown using Lyapunov theory.
– Name: Format
  Label: File Description
  Group: SrcInfo
  Data: electronic
– Name: URL
  Label: Access URL
  Group: URL
  Data: <link linkTarget="URL" linkTerm="https://lucris.lub.lu.se/ws/files/206302831/TASE_FINAL.pdf" linkWindow="_blank">https://lucris.lub.lu.se/ws/files/206302831/TASE_FINAL.pdf</link>
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsswe&AN=edsswe.oai.portal.research.lu.se.publications.e953e5f3.42c4.49f3.a6dd.39e7b844d42d
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1109/TASE.2024.3508718
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 9571
    Subjects:
      – SubjectFull: Engineering and Technology
        Type: general
      – SubjectFull: Electrical Engineering
        Type: general
      – SubjectFull: Electronic Engineering
        Type: general
      – SubjectFull: Information Engineering
        Type: general
      – SubjectFull: Control Engineering
        Type: general
      – SubjectFull: Teknik
        Type: general
      – SubjectFull: Elektroteknik och elektronik
        Type: general
      – SubjectFull: Reglerteknik
        Type: general
      – SubjectFull: Robotics and automation
        Type: general
      – SubjectFull: Robotik och automation
        Type: general
    Titles:
      – TitleFull: Model-Based Predictive Impedance Variation for Obstacle Avoidance in Safe Human–Robot Collaboration
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Salt Ducaju, Julian
      – PersonEntity:
          Name:
            NameFull: Olofsson, Björn
      – PersonEntity:
          Name:
            NameFull: Johansson, Rolf
      – PersonEntity:
          Name:
            NameFull: Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Engineering Health, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Teknik för hälsa, Originator
      – PersonEntity:
          Name:
            NameFull: Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator
      – PersonEntity:
          Name:
            NameFull: Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Automatic Control, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för reglerteknik, Originator
      – PersonEntity:
          Name:
            NameFull: Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator
      – PersonEntity:
          Name:
            NameFull: Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 15455955
            – Type: issn-locals
              Value: SWEPUB_FREE
            – Type: issn-locals
              Value: LU_SWEPUB
          Numbering:
            – Type: volume
              Value: 22
          Titles:
            – TitleFull: IEEE Transactions on Automation Science and Engineering
              Type: main
ResultId 1