Computer-Automated Evolution of an X-Band Antenna for NASA's Space Technology 5 Mission

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.

From evolutionary computation to the evolution of things

“…One appealing example from the design domain concerns X-band antennas for NASA's ST5 spacecraft 27 . The normal approach to this task is very time and labour intensive, relying heavily on expert knowledge.…”

Heuristic assessment of bridge scour sensitivity using differential evolution: case study for linking floodplain encroachment and bridge scour

“…Optimization has been coupled with process-based models of varying complexity to minimize the cost of groundwater remediation or monitoring (Deschaine et al 2013), to design the shape of a radio antenna for satellites (Hornby et al 2011), to optimize the control of hydroelectric power plants, and for many other applications (Bartholomew-Biggs et al 2002;Jeongwoo and Papalambros 2010;Marsden et al 2004;Mugunthan et al 2005;Shlomi et al 2010).…”

“…DE has been successfully used on a cost function containing an implicit weighting of multiple objectives, resulting in a significantly improved design (Hornby et al 2011). These kinds of tradeoffs encoded in a cost or fitness function have been discussed and utilized in applications including satellite antenna design (Hornby et al 2011), optimizing the performance and operation of hydroelectric power plants (Li et al 2015), and optimal management of groundwater remediation and management (Deschaine et al 2013;Rizzo and Dougherty 1996).…”

The Dematerializing Interface

“…'I believe that affordances result from the mental interpretation of things, based on our past knowledge and experience applied to our perception of the things about us' (Norman 2002, 219 fn). 2 Evolutionary algorithms were used to design 'the first computer-evolved antenna' for NASA's Space Technology 5 Mission, which launched three satellites in 2006 (Spector 2005, Hornby et al 2011 In 2011, almost four in ten US households owned two vehicles; nearly one in five owned three or more vehicles (US Department of Energy 2013). 4 See The Darpa Grand Challenge (2014).…”