The researchers experimented with a swarm of sugar-cube-size antlike robots called “Alices.” A camera followed the Alices’ movements and used a video projector above the robots to lay down trails of light marking where the robots had traveled — similar to the way real ants lay down chemical trails of pheromones.
The robots were programmed to follow light trails with a pair of light sensors, avoid obstacles and otherwise move forward, randomly changing the angle at which they moved every few seconds. The robots lacked more sophisticated navigation techniques.
At the beginning of the experiment, in which the branches of the maze had no light trail, the robots simply moved forward at random angles. If the robots detected a light trail, they would follow that path. This basic strategy naturally led the robots to choose the path that diverged least from their trajectory at each fork…
“The robots show that you don’t need complex cognitive processes to navigate these mazes,” Garnier said.
…”The principles that ants use to find shorter paths have actually been the basis of computer programs developed in the last 10 years to help decide what are the best paths for trucks to transport merchandise between cities, the so-called traveling salesman problem,” Garnier said. “One of the most efficient algorithms to solve this problem is directly inspired by the same logic studied in our work, and is also used by telecommunications companies to route packets of information between cell phones.”