I love swarm bots of all types. Something so innocent about them. Researchers from Georgia Tech have developed a method that allows “simple” robots — those without sensors, onboard processing power, communication capabilities — to perform complex tasks by leveraging their physical characteristics, a trait they term “task embodiment.” Think of it like trying to control a child, which is hard enough, and then trying to control many of them at once, which is nearly impossible. The same can be said for trying to get swarms of robots to work collectively without complex programming and a ton of onboard sensors.
To that end, the team designed BOBbots (Behaving, Organizing, Buzzing, bots), simplistic robots designed with a cylindrical chassis, vibrating brushes underneath, and a series of looser magnets that enable them to remain in areas longer when other robots are around. As these “dumb” robots (essentially mobile granular particles) move and bump into one another, compact aggregates form capable of collectively clearing debris that is too heavy for just one robot to move on its own.
The cooperation system was inspired by a theoretical model of particles moving around on a chessboard, which led the researchers to develop what they term “a self-organized particle system.” This allowed them to incorporate probability theory, statistical physics, and stochastic algorithms into their system to prove the BOBbots undergo a phase change as magnetic interactions increase. Meaning the robots go from a dispersed pattern to an aggregated or collective state to perform complex tasks. The breakthrough will pave the way for engineers to program collective swarms of simple robots without the need for complex algorithms or sophisticated hardware.