Unlike most human-engineered systems, biological
systems are emergent from low-level interactions, allowing
much broader diversity and superior adaptation to the complex
environments. Inspired by the process of morphogenesis in
nature, a bottom-up design approach for robot morphology
is proposed to treat a robot’s body as an emergent response
to underlying processes rather than a predefined shape. This
work presents Loopy, a “Swarm-of-One” polymorphic robot
testbed that can be viewed simultaneously as a robotic swarm
and a single robot. Loopy’s shape is determined jointly by
self-organization and morphological computing using physically
linked homogeneous cells. Experimental results show that
Loopy can form symmetric shapes consisting of lobes. Using
the the same set of parameters, even small amounts of initial
noise can change the number of lobes formed. However, once in
a stable configuration, Loopy has an “inertia” to transfiguring
in response to dynamic parameters. By making the connections
among self-organization, morphological computing, and robot
design, this works lays the foundation for more adaptable robot
designs in the future.
This is the abstract from a Loopy paper to be presented at IROS 2023: arxiv.org/abs/...
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