Linear Genetic Programming-Based Controller for Space Debris Retrieval

Created by W.Langdon from gp-bibliography.bib Revision:1.7810

@InProceedings{Gregson:2020:ICACR,

• author = "E. Gregson and M. L. Seto",
• title = "Linear Genetic Programming-Based Controller for Space Debris Retrieval",
• booktitle = "2020 4th International Conference on Automation, Control and Robots (ICACR)",
• year = "2020",
• pages = "112--121",
• 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.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ICACR51161.2020.9265513",
• month = oct,
• notes = "Also known as \cite{9265513}",

}

Genetic Programming entries for E Gregson M L Seto

Citations