Evolving a Bipedal Robot Controller
Created by W.Langdon from
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- @Misc{oai:CiteSeerX.psu:10.1.1.596.3170,
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title = "Evolving a Bipedal Robot Controller",
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author = "Michael Johnson",
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year = "2004?",
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keywords = "genetic algorithms, genetic programming",
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size = "1 page",
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abstract = "Research activity into developing bipedal humanoid
robots has recently been on the increase. Humanoid
robots are well suited for navigating environments
created for humans, and have the potential to perform
well on uneven terrain. Bipedal locomotion is a crucial
area of interest, and the problems it presents are not
yet fully solved. This poster discusses the simulation
of a bipedal robot and the use of Genetic Programming
techniques to evolve bipedal locomotion. Genetic
Programming is a technique that uses the principles of
natural selection to evolve programs. It allows
computers to learn to solve problems without being
explicitly programmed (Koza, 1992). The aim of the
project is to apply Genetic Programming techniques to
evolve a robot controller that is able to walk without
having to explicitly describe the gait. When evolving a
robot controller, it is not practical to use real
hardware to test the fitness of individuals. The
repeated testing would quickly wear out the hardware.
Instead, by using a simulation we can happily subject
our",
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annote = "The Pennsylvania State University CiteSeerX Archives",
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bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
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language = "en",
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oai = "oai:CiteSeerX.psu:10.1.1.596.3170",
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rights = "Metadata may be used without restrictions as long as
the oai identifier remains attached to it.",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.596.3170",
- }
Genetic Programming entries for
Michael Johnson
Citations