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Software-Driven Calibration Method for a Pick-and-Place Process

Kalvenes, Rasmus LU and Joelsson, Oskar (2024) In CODEN:LUTEDX/TEIE EIEM01 20241
Industrial Electrical Engineering and Automation
Abstract
Machine calibration is important for optimal performance throughout the lifespan of industrial processes. A prime example is the pick-and-place process, where robots must manipulate objects accurately. Currently, this process is manually calibrated, which can be a complex practice. This thesis studies a software-based approach to error detection within the process, aiming to reduce the need for manual calibration.

By utilizing existing sensors within the process, the method identifies translation and rotational errors within the system. The proposed approach involves measuring and comparing the perspective of mechatronic devices observing the same object. Thus, the di↵erences in perspectives can be identified and compensated for.

The... (More)
Machine calibration is important for optimal performance throughout the lifespan of industrial processes. A prime example is the pick-and-place process, where robots must manipulate objects accurately. Currently, this process is manually calibrated, which can be a complex practice. This thesis studies a software-based approach to error detection within the process, aiming to reduce the need for manual calibration.

By utilizing existing sensors within the process, the method identifies translation and rotational errors within the system. The proposed approach involves measuring and comparing the perspective of mechatronic devices observing the same object. Thus, the di↵erences in perspectives can be identified and compensated for.

The findings indicate promising results, demonstrating that the process could be cal- ibrated with an accuracy of a few millimeters using the proposed method. Moreover, the method is cost-e↵ective and quick to execute.

In summary, this thesis demonstrates the possibility of implementing a software-based approach for calibrating the pick-and-place process. This approach has been demon- strated to be accurate, quick, and simple to use, making it a potential alternative to manual calibration. (Less)
Please use this url to cite or link to this publication:
author
Kalvenes, Rasmus LU and Joelsson, Oskar
supervisor
organization
alternative title
En mjukvarubaserad kalibreringsmetod för en pick-and-place-process
course
EIEM01 20241
year
type
H3 - Professional qualifications (4 Years - )
subject
publication/series
CODEN:LUTEDX/TEIE
report number
5518
language
English
id
9170029
date added to LUP
2024-10-02 15:40:59
date last changed
2024-10-02 15:40:59
@misc{9170029,
  abstract     = {{Machine calibration is important for optimal performance throughout the lifespan of industrial processes. A prime example is the pick-and-place process, where robots must manipulate objects accurately. Currently, this process is manually calibrated, which can be a complex practice. This thesis studies a software-based approach to error detection within the process, aiming to reduce the need for manual calibration.

By utilizing existing sensors within the process, the method identifies translation and rotational errors within the system. The proposed approach involves measuring and comparing the perspective of mechatronic devices observing the same object. Thus, the di↵erences in perspectives can be identified and compensated for.

The findings indicate promising results, demonstrating that the process could be cal- ibrated with an accuracy of a few millimeters using the proposed method. Moreover, the method is cost-e↵ective and quick to execute.

In summary, this thesis demonstrates the possibility of implementing a software-based approach for calibrating the pick-and-place process. This approach has been demon- strated to be accurate, quick, and simple to use, making it a potential alternative to manual calibration.}},
  author       = {{Kalvenes, Rasmus and Joelsson, Oskar}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{CODEN:LUTEDX/TEIE}},
  title        = {{Software-Driven Calibration Method for a Pick-and-Place Process}},
  year         = {{2024}},
}