<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Roveda, Loris</dc:creator>
  <dc:creator>Bussolan, Andrea</dc:creator>
  <dc:creator>Braghin, Francesco</dc:creator>
  <dc:creator>Piga, Dario</dc:creator>
  <dc:date>2020</dc:date>
  <dc:description xmlns:ns0="xml" ns0:lang="en">Industrial robots are commonly used to perform interaction tasks (such as assemblies or polishing), requiring the robot to be in contact with the  surrounding environment. Such environments are (partially) unknown to the robot controller. Therefore, there is the need to implement interaction  controllers capable of suitably reacting to the established contacts. Although standard force controllers require force/torque measurements to  close the loop, most of the industrial manipulators do not have installed force/torque sensor(s). In addition, the integration of external sensors  results in additional costs and implementation effort, not affordable in many contexts/applications. To extend the use of compliant controllers to  sensorless interaction control, a model-based methodology is presented in this paper for the online estimation of the interaction wrench,  implementing a 6D virtual sensor. Relying on sensorless Cartesian impedance control, an Extended Kalman Filter (EKF) is proposed for the  interaction wrench estimation. The described approach has been validated in simulations, taking into account four different scenarios. In addition,  experimental validation has been performed employing a Franka EMIKA panda robot. A human–robot interaction scenario and an assembly task  have been considered to show the capabilities of the developed EKF, which is able to perform the estimation with high bandwidth, achieving  convergence with limited errors.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>https://localhost:5000/ark:/12658/srd1319395</dc:identifier>
  <dc:identifier>https://susi.usi.ch/global/documents/319395</dc:identifier>
  <dc:identifier>https://susi.usi.ch/documents/319395/files/Roveda_m_2020.pdf</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.3390/machines8040067</dc:relation>
  <dc:relation>info:eu-repo/semantics/altIdentifier/ark/12658/srd1319395</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>CC BY</dc:rights>
  <dc:source>Machines. - MDPI. - 2020, vol. 8, no. 4, p. 17</dc:source>
  <dc:subject xmlns:ns1="xml" ns1:lang="en">Extended kalman filter</dc:subject>
  <dc:subject xmlns:ns2="xml" ns2:lang="en">Wrench estimation</dc:subject>
  <dc:subject xmlns:ns3="xml" ns3:lang="en">6D virtual sensor</dc:subject>
  <dc:subject xmlns:ns4="xml" ns4:lang="en">Sensorless cartesian impedance control</dc:subject>
  <dc:subject xmlns:ns5="xml" ns5:lang="en">Industrial robots</dc:subject>
  <dc:subject xmlns:ns6="xml" ns6:lang="en">Interaction robotized tasks</dc:subject>
  <dc:subject>info:eu-repo/classification/udc/004</dc:subject>
  <dc:title xmlns:ns7="xml" ns7:lang="en">6D virtual sensor for wrench estimation in robotized interaction tasks exploiting extended Kalman filter</dc:title>
  <dc:type>http://purl.org/coar/resource_type/c_6501</dc:type>
</oai_dc:dc>
