Complex biological forms reproduce by taking advantage
of an arbitrarily complex set of auto-catalyzing chemical
reactions. Biological life is n control of its own means
of reproduction, and this autonomy of design and manufacture
is a key element that has not yet been understood or reproduced
artificially. To this date, robots-forms of artificial
life-are still designed laboriously and constructed by
teams of human engineers at great cost. Few robots are
available because these costs must be absorbed through
mass production that is justified only for toys, weapons,
and industrial systems like automatic teller machines.
In this discussion we report a set of experiments in
which simple electro- mechanical systems evolve from scratch
to yield physical locomoting machines. Like biological
lifeforms whose structure and function exploits the behaviors
afforded by their own chemical and mechanical medium,
our evolved creatures take advantage of the nature of
their own medium-thermoplastic, motors, and artificial
neurons. We thus achieve autonomy of design and construction
using evolution in a limited universe physical simulation,
coupled to off- the-shelf rapid manufacturing technology.
This is the first time robots have been robotically designed
and robotically fabricated.
Our key claim is that to realize artificial life, full
autonomy must be attained not only at the level of power
and behavior (the goal of robotics, today), but also at
the levels of design and fabrication. Only then can we
expect synthetic creatures to bootstrap and sustain their
own evolution. We thus seek automatically designed and
constructed physical artifacts that are (a) functional
in the real world, lb) diverse in architecture (possibly
each slightly different), and (c) producible in short
turn-around time, low cost, and large quantities. So far
these requirements have not been met.
The experiments described here use evolutionary computation
for design, and additive fabrication for reproduction.
The evolutionary process operates on a population of candidate
robots, each composed of some repertoire of building blocks.
The evolutionary process iteratively selects fitter machines,
creates offspring by adding, modifying, and removing building
blocks using a set of operators, and replaces them into
the population.
Our approach is based on use of only elementary building
blocks and operators in the design and fabrication process.
As building blocks are more elementary, any inductive
bias associated with them is minimized, and at the same
time architectural flexibility is maximized. Similarly,
use of elementary building blocks in the fabrication process
allows it to be more systematic and versatile. Starting
with a population of 200 machines that were comprised
initially of zero bars and zero neurons, we conducted
evolution in simulation. The fitness of a machine was
determined by its locomotion ability: the net distance
its center of mass moved on an infinite plane in a fixed
duration. The process iteratively selected fitter machines,
created offspring by adding, modifying and removing building
blocks, and replaced them into the population. This process
typically continued for 300 to 600 generations. Both body
(morphology) and brain (control) were thus co- evolved
simultaneously.
The simulator we used for evaluating fitness supported
quasi-static motion in which each frame is statically
stable. This kind of motion is simpler to transfer reliably
into reality, yet is rich enough to support low-momentum
locomotion. Typically, several tens of generations passed
before the first movement occurred. Various patterns of
evolutionary dynamics emerged, some of which are reminiscent
of natural phylogenic trees.
Selected robots out of those with winning performance
were then automatically replicated into reality: their
bodies, which existed only as points and lines, were first
converted into a solid model with ball-joints and accommodations
for linear motors according to the evolved design.
This solidifying stage was performed by an automatic
program that combined pre-designed components describing
a generic bar, ball joint, and actuator. The virtual solid
bodies were then materialized using commercial rapid prototyping
technology.
In spite of the relatively simple task and environment
(locomotion over an infinite horizontal plane), surprisingly
different and elaborate solutions were evolved. Machines
typically contained around 20 building blocks, sometimes
with significant redundancy (perhaps to make mutation
less likely to be catastrophic). Not less surprising was
the fact that some exhibited symmetry, which was neither
specified nor rewarded anywhere in the code; a possible
explanation is that symmetric machines are more likely
to move in a straight line, consequently covering a greater
net distance and acquiring more fitness. Similarly, successful
designs appear to be robust in the sense that changes
to bar lengths would not significantly hamper their mobility.
In summary, while both the machines and task described
in this work are fairly simple from the perspective of
what human teams of engineers can produce, and what biological
evolution has produced, we have demonstrated for the first
time a robotic bootstrap, where automatically designed
electromechanical systems have been manufactured robotically.
We have carefully minimized human intervention both in
the design and in the fabrication stages. Besides snapping
in the motors, the only human work was in informing the
simulation about the universe that could be manufactured.
This is the first time any artificial evolution system
has been connected to an automatic physical construction
system. Our evolutionary design system, solidification
process, and rapid prototyping machine form a primitive
"replicating" robot. While there are many, many further
steps before this technology is dangerous, we believe
that if indeed artificial systems are to ultimately interact
and integrate with reality, they cannot remain virtual;
it is crucial that they cross the simulation-reality gap
to learn, evolve, and affect the physical world directly.
Eventually, the evolutionary process must accept feedback
from the live performance of its products.
