When it comes to collective effort, laziness pays off
The physics of ant colonies yields clues for robot swarms and road traffic control. Natalie Parletta reports.
Humans have much to learn from ants, it seems. Researchers have now discovered from their behaviour how a busy work flow can be optimised – and surprisingly it’s not by everyone working harder. In fact, laziness may have its virtues in the right context.
The team, led by physicist Daniel Goldman from the Georgia Institute of Technology in Atlanta, US, observed that when colonies of fire ants (Solenopsis spp) were digging complex nest tunnels, only 30% of them were working at any given time.
It turns out, as reported in the journal Science, that this is the most efficient way to avoid traffic jams and keep the work flowing with minimal effort.
“We found a functional, community benefit to this seeming inequality in the work environment,” says Goldman. “Without it, digging just doesn’t get done.”
Despite functionally narrow tunnels with barely enough room for two ants to pass, the insects avoided clogging by withdrawing from tunnels already occupied, or by being idle.
The researchers, who are interested in the physics of living systems, tested this strategy on autonomous robots, which they say could be used for missions such as disaster recovery, mining or digging underground shelters.
“If you were a robot swarm on Mars and needed to dig deeply in a hurry to get away from dust storms, this strategy might help provide shelter without having perfect information about what everybody was doing,” Goldman muses.
The scientists discovered that up to three robots could work efficiently in a narrow tunnel, digging 3D-printed magnetic plastic balls designed to emulate sticky soil.
“When we put four robots into a confined environment and tried to get them to dig, they immediately jammed up,” says Goldman.
But when they adopted the ants’ approach, the robots were able to dig more quickly while expending less energy.
The team programmed the robots with various combinations of behaviours, which they termed “eager,” “reversal,” or “lazy.” When four robots dug eagerly, they got in each other’s way. Reversal prevented jams. But in terms of energy used, the lazy approach was the most efficient.
To understand the mechanisms and constraints of these strategies, the team used computer modelling similar to that used by traffic engineers.
“On highways, too few cars don’t provide much flow, while too many cars create a jam,” Goldman explained.
There is thus an intermediate level where things work best. The researchers learned that the ants were cleverly working at the peak of the model, with the optimal mix of behaviours to maximise efficiency and avoid jamming.
Goldman says the research not only throws more light on the sophisticated social skills of ants but provides insights into the physics of “task-oriented active matter” and “phenomena such as swarms”.