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Calibration of robot kinematics using a double ball-bar with embedded sensing

Brand, Sebastian and Nilsson, Niklas (2016)
Department of Automatic Control
Abstract
Today’s industrial robots are highly repeatable, but need to be calibrated to improve their absolute accuracy. This calibration can be done on many of the robot properties such as kinematic parameters, joint friction or bending stiffness. This thesis explores a calibration procedure for the kinematic parameters, that use a specialized piece of
hardware - the double ball-bar.
The double ball-bar restricts the motion of the robot to a spherical surface. Sensors were added to the ball-bar joints, which made it possible to use the forward kinematic homogeneous transformation matrix from both the robot side and the ball-bar side, the matrices can be compared to each other and the parameters of the robot can be identified using a non-linear... (More)
Today’s industrial robots are highly repeatable, but need to be calibrated to improve their absolute accuracy. This calibration can be done on many of the robot properties such as kinematic parameters, joint friction or bending stiffness. This thesis explores a calibration procedure for the kinematic parameters, that use a specialized piece of
hardware - the double ball-bar.
The double ball-bar restricts the motion of the robot to a spherical surface. Sensors were added to the ball-bar joints, which made it possible to use the forward kinematic homogeneous transformation matrix from both the robot side and the ball-bar side, the matrices can be compared to each other and the parameters of the robot can be identified using a non-linear least-squares minimization algorithm.
The calibration proved promising in simulations and showed an increased robustness to error sources such as white noise and fluctuations of the gear ratio found in cycloid drives. It also provided an improved identification of the robot parameters compared to the calibration done using the sensor-less double ball-bar.
In experiments the identification showed some improvement in the identification over using the sensor-less double ball-bar, but also that the method needs to be further improved to be able to produce satisfactory calibration results. (Less)
Please use this url to cite or link to this publication:
author
Brand, Sebastian and Nilsson, Niklas
supervisor
organization
year
type
H3 - Professional qualifications (4 Years - )
subject
report number
TFRT-6017
ISSN
0280-5316
language
English
id
8898906
date added to LUP
2017-01-16 13:39:10
date last changed
2017-01-16 13:39:10
@misc{8898906,
  abstract     = {Today’s industrial robots are highly repeatable, but need to be calibrated to improve their absolute accuracy. This calibration can be done on many of the robot properties such as kinematic parameters, joint friction or bending stiffness. This thesis explores a calibration procedure for the kinematic parameters, that use a specialized piece of
hardware - the double ball-bar.
 The double ball-bar restricts the motion of the robot to a spherical surface. Sensors were added to the ball-bar joints, which made it possible to use the forward kinematic homogeneous transformation matrix from both the robot side and the ball-bar side, the matrices can be compared to each other and the parameters of the robot can be identified using a non-linear least-squares minimization algorithm.
 The calibration proved promising in simulations and showed an increased robustness to error sources such as white noise and fluctuations of the gear ratio found in cycloid drives. It also provided an improved identification of the robot parameters compared to the calibration done using the sensor-less double ball-bar.
 In experiments the identification showed some improvement in the identification over using the sensor-less double ball-bar, but also that the method needs to be further improved to be able to produce satisfactory calibration results.},
  author       = {Brand, Sebastian and Nilsson, Niklas},
  issn         = {0280-5316},
  language     = {eng},
  note         = {Student Paper},
  title        = {Calibration of robot kinematics using a double ball-bar with embedded sensing},
  year         = {2016},
}