Amazing stuff!
"... Background: The term “active matter” refers to biological or technical systems from which larger structures are formed by means of self-organization. Such processes are based upon exclusively local interactions between identical, self-propelled units, such as amoebae or indeed robots.
Inspired by biological systems, ... authors propose a new model in which self-propelled agents communicate with each other. These agents recognize chemical, biological, or physical signals at a local level and make individual decisions using their internal machinery that result in collective self-organization. This orientation gives rise to larger structures, which can span multiple length scales.
The new paradigm of communicating active matter forms the basis of the study. Local decisions in response to a signal and the transmission of information, lead to collectively controlled self-organization.
... a possible application of the new model in soft robots – which is to say, robots that are made of soft materials. Such robots are suitable, for example, for performing tasks in human bodies. They can communicate with other soft robots via electromagnetic waves for purposes such as administering drugs at specific sites in the body. The new model can help nanotechnologists design such robot systems by describing the collective properties of robot swarms. ..."
From the abstract:
"The emergence of collective motion among interacting, self-propelled agents is a central paradigm in non-equilibrium physics. Examples of such active matter range from swimming bacteria and cytoskeletal motility assays to synthetic self-propelled colloids and swarming microrobots. Remarkably, the aggregation capabilities of many of these systems rely on a theme as fundamental as it is ubiquitous in nature: communication. ... Here we report on the multi-scale self-organization of interacting self-propelled agents that locally process information transmitted by chemical signals. We show that this communication capacity dramatically expands their ability to form complex structures, allowing them to self-organize through a series of collective dynamical states at multiple hierarchical levels. Our findings provide insights into the role of self-sustained signal processing for self-organization in biological systems and open routes to applications using chemically driven colloids or microrobots."
Self-organization: What robotics can learn from amoebae LMU researchers have developed a new model to describe how biological or technical systems form complex structures without external guidance.
Multi-scale organization in communicating active matter (open access)
Fig. 1: Schematics of the agent-based model for communicating active matter and summary of collective dynamic states.
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