  The giant single-celled slime mould Physarum polycephalum exhibits complex
morphological adaptation and amoeboid movement as it forages for food and may
be seen as a minimal example of complex robotic behaviour. Swarm computation
has previously been used to explore how spatiotemporal complexity can emerge
from, and be distributed within, simple component parts and their interactions.
Using a particle based swarm approach we explore the question of how to
generate collective amoeboid movement from simple non-oscillatory component
parts in a model of P. polycephalum. The model collective behaves as a cohesive
and deformable virtual material, approximating the local coupling within the
plasmodium matrix. The collective generates de-novo and complex oscillatory
patterns from simple local interactions. The origin of this motor behaviour is
distributed within the collective rendering is morphologically adaptive,
amenable to external influence, and robust to simulated environmental insult.
We show how to gain external influence over the collective movement by
simulated chemo-attraction (pulling towards nutrient stimuli) and simulated
light irradiation hazards (pushing from stimuli). The amorphous and distributed
properties of the collective are demonstrated by cleaving it into two
independent entities and fusing two separate entities to form a single device,
thus enabling it to traverse narrow, separate or tortuous paths. We conclude by
summarising the contribution of the model to swarm based robotics and
soft-bodied modular robotics and discuss the future potential of such material
approaches to the field.
