Individual ants are relatively simple creatures and yet a colony of ants can perform very complex tasks, such as intricate construction, foraging and defense.

Recently, Harvard researchers took inspiration from ants to design a team of relatively simple robots that can work collectively to perform complex tasks using only a few basic settings.

The research has been published in eLife.

“This project has continued with an abiding interest in understanding the collective dynamics of social insects such as termites and bees, in particular how these insects can manipulate the environment to create complex functional architectures,” said L Mahadevan, Lola England Valpine Professor of Applied Mathematics. , organismal and evolutionary biology, and physics, and senior author of the article.

The research team began by studying how black carpenter ants work together to burrow and escape from a soft corral.

“At first, the ants inside the corral moved around randomly, communicating via their antennae before they began working together to escape the corral,” said S Ganga Prasath, Harvard John A. Paulson postdoctoral fellow. School of Engineering and Applied Sciences and one of the main authors of the article.

Ants primarily rely on their antennae to interact with the environment and other ants, a process called antennae. The researchers observed that the ants spontaneously congregated around areas where they interacted more often. Once a few ants started tunneling through the corral, others soon joined. Over time, the excavation at one of these places proceeded more quickly than at others, and the ants eventually dug a tunnel out of the corral.

From these observations, Mahadevan and his team identified two relevant parameters for understanding the ants’ excavation task; the strength of collective cooperation and the pace of excavations. Numerical simulations of mathematical models that encode these parameters have shown that ants can only dig successfully when they cooperate strongly enough with each other while simultaneously digging efficiently.

Driven by this understanding and building on the models, the researchers built robotic ants, dubbed Rants, to see if they could work together to escape from a similar corral. Instead of chemical pheromones, the RAnts used “photormones”, fields of light left behind by the traveling RAnts that mimic pheromone fields or the antenna.

The RAnts were programmed only via simple local rules: follow the gradient of the photoromone field, avoid other robots where the photoromone density was high, and pick up obstacles where the photoromone density was high and drop them where the photoromone was weak. These three rules allowed RAnts to quickly escape confinement and, just as importantly, also allowed researchers to explore regions of behavior that are difficult to detect with real ants.

“We have shown how cooperative execution of tasks can arise from simple rules and such rules of similar behavior can be applied to solve other complex issues such as construction, search and rescue and defence,” Prasath said.

This approach is very flexible and robust to detection and control errors. It could be extended and applied to teams of dozens or hundreds of robots using a range of different types of communication fields. It is also more resilient than other collaborative problem-solving approaches. Even if a few individual robot units fail, the rest of the team can complete the task.

“Our work, combining laboratory experiments, theory and robotic mimicry, highlights the role of a malleable environment as a communication channel, where self-reinforcing signals lead to the emergence of cooperation and thus to the solution of complex problems. Even without representation, planning, or global optimization, the interplay between simple local rules at the individual level and the embodied physics of the collective leads to intelligent behavior and is therefore likely to be relevant more broadly,” Mahadevan said.