Calibration of the Robotic Arm with Corrections using Local Linear Neuro-fuzzy Models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F22%3A00362039" target="_blank" >RIV/68407700:21220/22:00362039 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.17973/MMSJ.2022_12_2022160" target="_blank" >https://doi.org/10.17973/MMSJ.2022_12_2022160</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.17973/MMSJ.2022_12_2022160" target="_blank" >10.17973/MMSJ.2022_12_2022160</a>

Result language
angličtina
Original language name
Calibration of the Robotic Arm with Corrections using Local Linear Neuro-fuzzy Models
Original language description
The paper deals with the enhancement of the robotic arm calibration using corrections based on local linear neuro-fuzzy models. After the standard calibration of the geometric parameters in the robot's kinematic model, there are still residual errors between the measured positions and the positions predicted by the model. The source of these errors are various non-geometric parameters and nonlinear phenomena that traditional kinematic calibration models do not include. The neuro-fuzzy model based on a locally linear model tree can approximate the residual error as a function of the robot's joint angles. Adding this approximation to the output of the calibrated robot model significantly increases the accuracy of the end-effector position. The results of the described method were verified and compared with other approaches on a simulation model of a flexible planar two-link mechanism. Experimental verification was performed on an industrial robot Stäubli TX200 with data measured by Leica laser tracking device.
Czech name
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Czech description
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Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
20302 - Applied mechanics

Project
<a href="/en/project/EF16_026%2F0008404" target="_blank" >EF16_026/0008404: Machine Tools and Precision Engineering</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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