MLP Neural Network for a Kinematic Control of a Redundant Planar Manipulator

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F22%3A00352317" target="_blank" >RIV/68407700:21220/22:00352317 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-83594-1_3" target="_blank" >https://doi.org/10.1007/978-3-030-83594-1_3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-83594-1_3" target="_blank" >10.1007/978-3-030-83594-1_3</a>

Result language
angličtina
Original language name
MLP Neural Network for a Kinematic Control of a Redundant Planar Manipulator
Original language description
A non-redundant manipulator inverted kinematics can be easily solved by a multilayer perceptron neural network. For redundant manipulators, the inverted function cannot exist. Many advanced types of neural networks have been used at least for kinematic and dynamic control. This article describes a solution, when the redundancy is compensated by a simple quality function, which serves at the same time as a solution of the obstacle avoidance problem. This additional function is not combined with the functions describing the manipulator forward kinematics, but is applied to the data, prepared for the network training. This makes the whole process much simpler to realize, although the preparation of data for the training is computationally demanding.
Czech name
—
Czech description
—

Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

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

Similar results(10)