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Kinematic Calibration of a Collaborative Robot by a Marker Based Optical Measurement Procedure

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Intelligent Autonomous Systems 17 (IAS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 577))

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Abstract

Static robot calibration determines the parameters of a mathematical model that approximates as closely as possible the relationship between the end-effector pose of a robot and its corresponding actuated joint variables. The manufacturer of a robot delivers such a set of parameters but in principle more accurate own measurements can be used to determine optimized parameters. The purpose of this paper is 1. to show how much the position accuracy of robots of type UR5e from Universal Robots can be increased by application of a marker based optical measurement procedure based on circle fits and 2. what are the limitations of this procedure. Furthermore it is described how to use so called modified Denavit-Hartenberg parameters instead of the typically used distal/classical definition to achieve comparability between different measurements. Overall it is shown that with the calibration procedure the errors can be reduced in practice but only less for a a brand-new robot and with usage of the manufacturer calibration data set. The remaining errors show a specific structure, which suggests that the mechanical stability of the robot limits the positioning accuracy and not the accuracy of the measurement procedure to determine the DH-parameters.

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Notes

  1. 1.

    https://www.karlsruhe.dhbw.de/rahmlab.

  2. 2.

    https://www.vicon.com/hardware/devices/calibration/.

  3. 3.

    https://www.vicon.com/software/tracker/.

  4. 4.

    http://jdataaquisition.orat.de.

  5. 5.

    https://github.com/MobMonRob/JViconDataStream2.

  6. 6.

    https://www.artiminds.com/de/produkte-und-leistungen/robot-programming-suite-basic/.

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Correspondence to Oliver Rettig .

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Rettig, O., Müller, S., Strand, M. (2023). Kinematic Calibration of a Collaborative Robot by a Marker Based Optical Measurement Procedure. In: Petrovic, I., Menegatti, E., Marković, I. (eds) Intelligent Autonomous Systems 17. IAS 2022. Lecture Notes in Networks and Systems, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-031-22216-0_32

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