Geometrical calibration and uncertainty estimation methodology for a novel self-propelled miniature robotic machine tool

Aitor Olarra, Dragos Axinte, Gorka Kortaberria

Research output: Journal PublicationArticlepeer-review

17 Citations (Scopus)

Abstract

This paper reports on a novel calibration method which enables completely automatic identification of the kinematics of a walking hexapod robotic machine tool. The method uses three on-board cameras and relies on a coupled model that combines kinematics and photogrammetry. Both the mathematical modelling and the actual implementation are detailed. Besides the calibration method, the paper proposes an analytical methodology to estimate the uncertainties of the identified kinematical parameters. The methodology is validated against both experimental results and against previously reported observability indexes. This methodology enables moving from qualitative indexes, observability indexes, to quantitative estimations. The methodology is applied to guaranty a calibration configuration that allows estimating the robot parameters with an uncertainty of 0.1 mm due to non-repeatability of the measurements.

Original languageEnglish
Pages (from-to)204-214
Number of pages11
JournalRobotics and Computer-Integrated Manufacturing
Volume49
DOIs
Publication statusPublished - Feb 2018
Externally publishedYes

Keywords

  • Hexapod
  • Kinematical calibration
  • Observability index
  • Parallel kinematic machine
  • Parameter identification
  • Uncertainty

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mathematics (all)
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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