Accuracy of the Inverse Kinematics of a Planar Redundant Manipulator Solved by an MLP Neural Network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F24%3A00377356" target="_blank" >RIV/68407700:21220/24:00377356 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-70251-8_22" target="_blank" >https://doi.org/10.1007/978-3-031-70251-8_22</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-70251-8_22" target="_blank" >10.1007/978-3-031-70251-8_22</a>
Alternative languages
Result language
angličtina
Original language name
Accuracy of the Inverse Kinematics of a Planar Redundant Manipulator Solved by an MLP Neural Network
Original language description
The inverse kinematics of manipulators can be solved by approximating the data obtained using forward kinematics through the use of a multi-layer perceptron neural network, provided the input and output data are swapped before training. However, with redundant manipulators, reaching the same point is possible with an infinite number of joint angle settings, rendering the existence of an inverse function impossible. Data for training the neural network must be prepared so that only one combination of angles is used for each point reached. Achieving this may involve supplementing the obstacle avoidance function, even though the forward kinematics of the manipulator lacks a clear, analytically accessible solution. The paper addresses how to find a solution to forward kinematics that optimally fulfills the function describing the obstacle avoidance problem, ensuring uniqueness and continuity for use in neural network training. The acquired data were used to train a neural network with one hidden layer, and the accuracy of the resulting network was verified on a simple trajectory.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20204 - Robotics and automatic control
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Mechanism Design IV
ISBN
978-3-031-70250-1
ISSN
2211-0984
e-ISSN
—
Number of pages
10
Pages from-to
202-211
Publisher name
Springer Science+Business Media B.V.
Place of publication
Dordrecht
Event location
Liberec
Event date
Sep 3, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001328769400022