A herd of wild horses grazes peacefully on a meadow. Suddenly, a potential predator appears, and they flee. But how do they manage to do so collectively?
Researchers in Germany have been exploring how animals must behave in order to initiate an efficient flight response.
University of Konstanz researchers Chun-Jen Chen and Professor Clemens Bechinger, a member of the university’s Centre for the Advanced Study of Collective Behaviour, set about examining the issue using microrobots that act like a group of animals.
The two physicists found that a swarm of animals – taken as a whole – can complete an optimum flight response, even if individual animals do not notice the threat or they react the wrong way.
The starting point for their work was to consider a group of peacefully swirling animals and what would happen if it suddenly encountered a dangerous situation.
For their experiments, described in the March 7 issue of the New Journal of Physics, the study team employed a system of microrobots, comprised of glass balls that are programmable, active, and spread out finely within a certain area.
When the beads are lit using a focused laser beam, one side of them warms up and causes them to move, like animals.
“We are able to target each individual bead and adjust its movement to fit that of its neighbours,” explains Chen, who is completing his doctorate in Bechinger’s research team, and who was mainly responsible for completing the experiments.
“The robots in our swarm are programmed to avoid collisions. They also received the information that they were to orient their motion based on the location of the approximate middle of the group.”
With the help of these rules, the robots organized themselves into a swirl. The researchers found that the microrobotic swarm reproduces the movements of real animal swarms surprisingly well.
As soon as a predator appears, the microrobots change their movements, Bechinger says.
However, the change in direction is only minimal and does not cause each member of the swarm to move directly away from the predator at any given time. It is striking, however, that the group as a whole moves in a straight line away from the predator.
“This feat in which individuals move in a way that is not ideal for each one of them, but where the group as a whole behaves optimally, is based on a collective decision-making process or ‘swarm intelligence’ where information is constantly being exchanged between different members of a group,” Bechinger says.
“One direct consequence of this behaviour is that the efficiency of the flight response remains virtually unchanged, even if half of the microrobots – or animals – do not respond to the threat,” Chen explains.
“This shows that missing or incomplete information from individual members of a group can be compensated by other members”.
They think this could possibly be one of the reasons why animals organize themselves in herds, even though herds are significantly easier for predators to spot than individual animals.
In addition to gaining a better understanding of the basis for decision-making in groups of animals, the research results are also relevant for applications in the field of microrobotics.
At the moment, different scenarios are being discussed in which multiple autonomous robots complete a useful task together and in which disruptions to communication between the robots would automatically cause problems.
With the knowledge gained from this study, a robotic swarm could work well even if, for example, the sensors in individual robots were to fail.
Bechinger adds: “The other microrobots would simply compensate for those with broken sensors, giving such systems a very high level of robustness”.
Chun-Jen Chen, Clemens Bechinger: Collective response of microrobotic swarms to external threats. New Journal of Physics. DOI https://doi.org/10.1088/1367-2630/ac5374