Evolving a Bipedal Robot Controller

Created by W.Langdon from gp-bibliography.bib Revision:1.7686

@Misc{oai:CiteSeerX.psu:10.1.1.596.3170,

• title = "Evolving a Bipedal Robot Controller",
• author = "Michael Johnson",
• year = "2004?",
• keywords = "genetic algorithms, genetic programming",
• size = "1 page",
• 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",
• annote = "The Pennsylvania State University CiteSeerX Archives",
• bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
• language = "en",
• oai = "oai:CiteSeerX.psu:10.1.1.596.3170",
• rights = "Metadata may be used without restrictions as long as the oai identifier remains attached to it.",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.596.3170",

}

Genetic Programming entries for Michael Johnson

Citations