Insects are masters of the swarm. Bugs like bees and termites and ants manage to do all sorts of complicated and productive things, despite the fact that on an individual level, each insect is really not that smart. The manifestation of complex behaviors from simple systems is appealing to roboticists who otherwise have to try to figure out all kinds of complicated localization and navigation tricks all by themselves. Researchers from the New Jersey Institute of Technology, in Newark, and at the Research Centre on Animal Cognition, in Toulouse, France, are using swarms of ant-like robots to efficiently navigate networks without any sort of cleverness at all.
These robots are called Alice, either collectively or as individuals. Their behavior is based on Argentine ants, and as such, they have very, very primitive sensing systems: little more than a couple of light sensors. The little robots were released into a simple network maze, where they wandered around a bit looking for an objective while trying to take the least number of turns possible. Wherever they went, they left a trail of "pheromones" as lights turned on above them. All of these behaviors are what ants do, and as you can see in the video, it turned into a very effective way of autonomously discovering an efficient path.
From the sound of things, this research wasn't intended to be about robots, but rather to use the robots to try and figure out how the ants manage to be all ant-y despite having tiny brains and lousy eyesight:
"This research suggests that efficient navigation and foraging can be achieved with minimal cognitive abilities in ants," says lead author Simon Garnier. "It also shows that the geometry of transport networks plays a critical role in the flow of information and material in ant as well as in human societies."
Evan Ackerman is a senior editor at IEEE Spectrum. Since 2007, he has written over 6,000 articles on robotics and technology. He has a degree in Martian geology and is excellent at playing bagpipes.
