Generative Representations for the Automated Design of
Modular Physical Robots
IEEE transactions on Robotics and Automation, 19 (4):
709--713 (August 2003)DOI: doi:10.1109/TRA.2003.814502
Abstract
The field of evolutionary robotics has demonstrated
the ability to automatically design the morphology and
controller of simple physical robots through synthetic
evolutionary processes. However, it is not clear if
variation-based search processes can attain the
complexity of design necessary for practical
engineering of robots. Here, we demonstrate an
automatic design system that produces complex robots by
exploiting the principles of regularity, modularity,
hierarchy, and reuse. These techniques are already
established principles of scaling in engineering design
and have been observed in nature, but have not been
broadly used in artificial evolution. We gain these
advantages through the use of a generative
representation, which combines a programmatic
representation with an algorithmic process that
compiles the representation into a detailed
construction plan. This approach is shown to have two
benefits: it can reuse components in regular and
hierarchical ways, providing a systematic way to create
more complex modules from simpler ones; and the evolved
representations can capture intrinsic properties of the
design space, so that variations in the representations
move through the design space more effectively than
equivalent-sized changes in a nongenerative
representation. Using this system, we demonstrate for
the first time the evolution and construction of
modular, three-dimensional, physically moving robots,
comprising many more components than previous work on
body-brain evolution.