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dc.contributor.authorAhmadiehkhanesar, Mojtaba
dc.contributor.otherAhmadiehkhanesar, Mojtaba
dc.coverage.spatialUniversity of Nottingham, Nottingham, UKen_UK
dc.description.abstractCollaborative Robot Static Anti-Gravity Data During the real industrial robot movement, robot joint angles, joint angular velocities, and joint motor currents are recorded via ROS-Melodic software which handles the communication (@~125Hz). Static data is then extracted by finding the sample points at which the robots angular velocities are equal to zero. Data is then formatted in Comma Separated Values (CSV) formatted data. This data can be exploited in machine learning approaches for static modelling of the industrial robot behavior. This data may be utilized research investigating static industrial robot model including its gravity terms and static friction terms. Data is composed of joint angle data: Positions_reduced.csv joint angular velocities: Velocities_reduced.csv joint motor currents: Efforts_reduced.csven_UK
dc.publisherThe University of Nottinghamen_UK
dc.subject.lcshMathematical modelsen_UK
dc.subject.lcshNeural networks (Computer science)en_UK
dc.subject.lcshRobots, Industrialen_UK
dc.titleUR5 collaborative robot static anti-gravity torque versus joint angle dataen_UK
dc.subject.freeRobotics, anti-gravity, static data, Estimation, friction, mathematical model, modeling, neural network modelen_UK
dc.subject.jacsEngineering::Mechanical engineering::Mechanisms & machinesen_UK
dc.subject.lcT Technology::TJ Mechanical engineering and machinery::TJ170 Mechanics applied to machinery. Dynamicsen_UK
dc.subject.lcQ Science::QC Physicsen_UK
uon.divisionUniversity of Nottingham, UK Campusen_UK
uon.funder.controlledEngineering & Physical Sciences Research Councilen_UK
uon.datatypeCSV data seten_UK
uon.collectionmethodData collected through ROS software using the sampling frequency of 125Hz via LAN connection between the UR5 robot and a PC running a Linux OSen_UK
uon.institutes-centresUniversity of Nottingham, UK Campusen_UK

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