Scientists use microbiotic swarms to measure animals’ susceptibility to threats.

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A herd of antelope grazes quietly in a meadow, but when a lion appears out of nowhere, the herd escapes.

But how do they do it as a group?

Chun-Jen Chen, physicist at the University of Konstanz, and Professor Clemens Bechinger, who is part of the excellence group “Center for the advanced study of collective behavior”.

In a study involving microrobots that behave like swarms of animals, researchers demonstrate that a swarm of animals as a whole completes a flawless flight response.

Animals that detect predators

(Photo: ASHRAF SHAZLY/AFP via Getty Images)

To avoid and respond to predation, animals must first notice the presence of a potential predator.

According to Naturerecognition of predator signals is necessary for the onset of anti-predator activity.

This may be inherent since animals may recognize predators as a threat even if they have never seen one before, or only learned after being exposed to a predator threat.

Animals can respond to general predatory risk indicators, such as a sudden movement or the presence of an impending object, as well as species cues, such as a scent or appearance, that allow them to make the distinction between carnivorous and non-predatory animals.

Many animals depend on the availability of many signs to accurately estimate the level of threat.

Animals are more likely to react if a higher number of clues are noticed, as this provides a more reliable indicator of the existence and identification of a predator.

Read also : Predator-prey relationship: where are all the lions?

A microbiotic swarm used for predators

The researchers began their analysis by visualizing a group of animals circling pleasantly and what would happen if they were suddenly confronted with a dangerous environment.

The researchers began their investigation by imagining a swarm of happily spinning creatures and what would happen if they were suddenly pushed into a threatening environment, according to ScienceDaily.

They can locate each bead and adjust its movement to match that of its neighbors, says Chen, who holds a Ph.D. student of Bechinger’s study team who was primarily responsible for finishing the experiments.

When a predator arrives, the microrobots adjust their movements, according to Bechinger.

The change in direction, however, is minor and does not cause every member of the swarm to move directly away from the predator at some point.

This feat, in which individuals move in a way that is not optimal for each of them but where the group as a whole acts optimally, is based on a process of collective judgment or “swarm intelligence”. , according to Bechinger, in which information is constantly exchanged between different members of a group.

The research results are useful for applications in the field of microrobotics as well as for gaining a better understanding of the foundations of decision-making in animal groups.

Several situations are currently detailed in which a large number of autonomous robots collaborate to perform meaningful work and where disruptions in communication between robots cause problems.

Thanks to the information collected in this study, a robotic swarm can operate successfully even if individual robot sensors fail, for example.

According to Chen, an immediate consequence of this behavior is that the effectiveness of the flight response remains almost the same even if half of the microrobots or animals do not respond to the threat.

This demonstrates that missing or partial information from individual members of the group can be compensated by other members.

Physicists believe this is one of the reasons why animals organize themselves into herds of seven, although herds are much easier for predators to notice than individual animals.

Related article: The decline of predators leaves prey in a sticky situation

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