The Complex Rheology And Biomechanics Lab (CRAB Lab) in the School of Physics at The Georgia Institute of Technology is developing new algorithms to show how swarms of very simple robots can be made to work together as a group.
“Our whole perspective is: What’s the simplest computational model that will achieve these complicated tasks?” said Dana Randall, a computer scientist at Georgia Tech and one of the lead researchers on the project. “We’re looking for elegance and simplicity.”
As a computer scientist, Randall thinks about the problem in algorithmic terms: What is the most basic set of instructions individual elements in a swarm can run, based on the meager data they can collect, that will lead inevitably to the complex collective behavior researchers want? This past November, Randall and colleagues published an algorithm that ensures that an idealized particle swarm will move in a coordinated manner.
The work with these robots, known as “smarticles,” is part of a broader interest in the feasibility and applications of self-organizing robots. Other examples include “droplet”-size robots being developed at the University of Colorado, “Kilobot” swarms at Harvard University, and swarmanoids out of a pioneering lab in Belgium. In many of these cases the idea is to mimic emergent phenomena found in nature, like the regimented motion of a decentralized colony of army ants or the unconscious, self-programming assembly of DNA molecules.
“We know what we want the collective to do, but in order to program it we need to know what each agent must be doing on the individual level,” said Melvin Gauci, a researcher at Harvard working on swarm robotics. “Going between those two levels is what’s very challenging.”
For more information, see:
The Georgia Institute of Technology paper, Phototactic Supersmarticles.
The Quantra Magazine video, Daniel Goldman and His Smart Robots.