Literature DB >> 20583909

Computer-automated evolution of an X-band antenna for NASA's Space Technology 5 mission.

Gregory S Hornby1, Jason D Lohn, Derek S Linden.   

Abstract

Whereas the current practice of designing antennas by hand is severely limited because it is both time and labor intensive and requires a significant amount of domain knowledge, evolutionary algorithms can be used to search the design space and automatically find novel antenna designs that are more effective than would otherwise be developed. Here we present our work in using evolutionary algorithms to automatically design an X-band antenna for NASA's Space Technology 5 (ST5) spacecraft. Two evolutionary algorithms were used: the first uses a vector of real-valued parameters and the second uses a tree-structured generative representation for constructing the antenna. The highest-performance antennas from both algorithms were fabricated and tested and both outperformed a hand-designed antenna produced by the antenna contractor for the mission. Subsequent changes to the spacecraft orbit resulted in a change in requirements for the spacecraft antenna. By adjusting our fitness function we were able to rapidly evolve a new set of antennas for this mission in less than a month. One of these new antenna designs was built, tested, and approved for deployment on the three ST5 spacecraft, which were successfully launched into space on March 22, 2006. This evolved antenna design is the first computer-evolved antenna to be deployed for any application and is the first computer-evolved hardware in space.

Mesh:

Year:  2010        PMID: 20583909     DOI: 10.1162/EVCO_a_00005

Source DB:  PubMed          Journal:  Evol Comput        ISSN: 1063-6560            Impact factor:   3.277


  7 in total

Review 1.  From evolutionary computation to the evolution of things.

Authors:  Agoston E Eiben; Jim Smith
Journal:  Nature       Date:  2015-05-28       Impact factor: 49.962

2.  Artificial intelligence exploration of unstable protocells leads to predictable properties and discovery of collective behavior.

Authors:  Laurie J Points; James Ward Taylor; Jonathan Grizou; Kevin Donkers; Leroy Cronin
Journal:  Proc Natl Acad Sci U S A       Date:  2018-01-16       Impact factor: 11.205

3.  Morphological Evolution of Physical Robots through Model-Free Phenotype Development.

Authors:  Luzius Brodbeck; Simon Hauser; Fumiya Iida
Journal:  PLoS One       Date:  2015-06-19       Impact factor: 3.240

4.  Neural modularity helps organisms evolve to learn new skills without forgetting old skills.

Authors:  Kai Olav Ellefsen; Jean-Baptiste Mouret; Jeff Clune
Journal:  PLoS Comput Biol       Date:  2015-04-02       Impact factor: 4.475

5.  Improving HybrID: How to best combine indirect and direct encoding in evolutionary algorithms.

Authors:  Lucas Helms; Jeff Clune
Journal:  PLoS One       Date:  2017-03-23       Impact factor: 3.240

6.  Evolutionary tinkering vs. rational engineering in the times of synthetic biology.

Authors:  Víctor de Lorenzo
Journal:  Life Sci Soc Policy       Date:  2018-08-12

7.  Evolution of oil droplets in a chemorobotic platform.

Authors:  Juan Manuel Parrilla Gutierrez; Trevor Hinkley; James Ward Taylor; Kliment Yanev; Leroy Cronin
Journal:  Nat Commun       Date:  2014-12-08       Impact factor: 14.919

  7 in total

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