  Exploration of asteroids and comets can give insight into the origins of the
solar system and can be instrumental in planetary defence and in-situ resource
utilization (ISRU). Asteroids, due to their low gravity are a challenging
target for surface exploration. Current missions envision performing
touch-and-go operations over an asteroid surface. In this work, we analyse the
feasibility of sending scores of nano-landers, each 1 kg in mass and volume of
1U, or 1000 cm3. These landers would hop, roll and fly over the asteroid
surface. The landers would include science instruments such as stereo cameras,
hand-lens imagers and spectrometers to characterize rock composition. A network
of nano-landers situated on the surface of an asteroid can provide unique and
very detailed measurements of a spacecraft impacting onto an asteroid surface.
A full-scale, artificial impact experiment onto an asteroid can help
characterize its composition and geology and help in the development of
asteroid deflection techniques intended for planetary defence. Scores of
nano-landers could provide multiple complementary views of the impact,
resultant seismic activity and trajectory of the ejecta. The nano-landers can
analyse the pristine, unearthed regolith shielded from effects of UV and cosmic
rays and that may be millions of years old. Our approach to formulating this
mission concepts utilizes automated machine learning techniques in the planning
and design of space systems. We use a form of Darwinian selection to select and
identify suitable number of nano-landers, the on-board instruments and control
system to explore and navigate the asteroid environment. Scenarios are
generated in simulation and evaluated against quantifiable mission goals such
as area explored on the asteroid and amount of data recorded from the impact
event.
