behavioural simulations |
in order to simulate a more automated, goal oriented movement sequence and communication between multiple bodies, a computational abstraction model was developed to emulate the same rotational movement around two simultaneous axis of the physical geometry.
the emulation was the first step into the understanding of the emergent behaviour that could come out of the collective behaviour and interaction of multiple machines. the computational simulations were important to expose the limits and pos- sibilities of the system and the defined families of creatures.
through simple embedded intelligence - such as maximum number of possible arrayed passives without active unit, reference and sticking to the ground, no self and ground interlocking, etc. - and simple goals - like find neighbours, reach or avoid and area – a body autonomously adjusts and optimizes its own movement sequence.
superbody formation |
when multiple bodies connects, their possibilities of action be- comes drastically more complex, joining forces to a combined su- perbody.
in this example, the bodies autonomously adjusts and optimiz- es its own movement sequence in order to combine into a super body, with broadened behaviour for the sake of reaching the goal.
autonomous decision making |
multiple bodies in a field must communicate as a type of aware- ness in order to find its closest and more proeminent neighbour to connect and form a superbody to perform specific tasks, in this case, reach the goal.
it’s possible to observe how different combinations results in dif- ferent behaviours even when they have a common objective