Forward Kinematics for 2 DOF Planar Robot using Linear Genetic Programming
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- @Article{DBLP:journals/rcs/ArellanoR19,
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author = "Humberto Velasco Arellano and Martin Montes Rivera",
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title = "Forward Kinematics for 2 {DOF} Planar Robot using
Linear Genetic Programming",
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journal = "Research in Computing Science",
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volume = "148",
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number = "6",
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pages = "123--133",
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year = "2019",
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keywords = "genetic algorithms, genetic programming, forward
kinematics, automatic robot modeling, linear genetic
programming",
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ISSN = "1870-4069",
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URL = "https://www.rcs.cic.ipn.mx/2019_148_6/Forward%20Kinematics%20for%202%20DOF%20Planar%20Robot%20using%20Linear%20Genetic%20Programming.pdf",
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timestamp = "Wed, 17 Feb 2021 00:00:00 +0100",
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biburl = "https://dblp.org/rec/journals/rcs/ArellanoR19.bib",
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bibsource = "dblp computer science bibliography, https://dblp.org",
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size = "11 pages",
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abstract = "In the field of robotics, forward kinematics is an
activity that allows finding a mathematical model for
the resulting position in the final effector based on
the robot joints position, a popular alternative for
determining this model is defined by the Denavit
Hartenberg convention, nevertheless, this method
requires knowledge about linear algebra and
three-dimensional spatial kinematics. Machine learning
uses specific computational methodologies to solving
similar problems in several areas, so it could be a
viable answer for automatic determining of forwarding
kinematics. we propose the use of genetic programming
as a machine learning algorithm for finding the forward
kinematics of a 2 degrees of freedom robot, getting a
satisfactory outcome obtaining a satisfactory result
with blocks that describe the expected solution,
validating the capacity of the genetic programming in
order to validate this algorithm for later work with
more complex robots.",
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notes = "https://www.rcs.cic.ipn.mx/",
- }
Genetic Programming entries for
Humberto Velasco Arellano
Martin Montes Rivera
Citations