Linear Genetic Programming-Based Controller for Space Debris Retrieval
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- @InProceedings{Gregson:2020:ICACR,
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author = "E. Gregson and M. L. Seto",
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title = "Linear Genetic Programming-Based Controller for Space
Debris Retrieval",
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booktitle = "2020 4th International Conference on Automation,
Control and Robots (ICACR)",
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year = "2020",
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pages = "112--121",
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abstract = "In this paper, we investigate the use of linear
genetic programming to evolve a controller that can
guide a debris removal chaser spacecraft to match the
motion of an uncontrolled target debris object. The
problem is treated in 2D, and the controller is
required to apply forces and torques to the chaser such
that it approaches the target and matches a {"}hand{"}
point in the chaser-fixed frame to a {"}handle{"} point
in the target-fixed frame. The training simulations are
extensively parameterized, and as the population of
controllers evolves, the population of training
scenarios also changes through both coevolution and
scheduled changes. This allows the controller
population to be gradually taught the full task after
starting with a simpler version. The resulting evolved
controllers show promise but would benefit from a more
sophisticated GP implementation than monolithic linear
GP.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/ICACR51161.2020.9265513",
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month = oct,
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notes = "Also known as \cite{9265513}",
- }
Genetic Programming entries for
E Gregson
M L Seto
Citations