Simple robots, intelligent algorithms – sciencedaily

Anyone who has children knows that while controlling one child can be difficult, controlling several at once can be almost impossible. Getting swarms of robots to work collectively can be just as difficult, unless researchers carefully choreograph their interactions – like planes in formation – using increasingly sophisticated components and algorithms. But what can be reliably accomplished when the available robots are simple, inconsistent, and lack sophisticated programming for coordinated behavior?

A team of researchers led by Dana Randall, ADVANCE professor of computer science and Daniel Goldman, professor of physics in the Dunn family, both at the Georgia Institute of Technology, sought to show that even the simplest of robots can still accomplish tasks. far beyond the capabilities of any one, or even a few of them. The goal of accomplishing these tasks with what the team dubbed “dumb robots” (essentially moving granular particles) exceeded their expectations, and researchers report being able to remove all sensors, communication, memory. and computation – and instead of accomplishing a set of tasks by taking advantage of the physical characteristics of robots, a trait the team calls “the embodiment of the task.”

The team BOBbots, or “behaving, organizing, buzzing bots” named for granular physics pioneer Bob Behringer, are “about as dumb as they get,” Randall explains. “Their cylindrical frame has vibrating brushes underneath and loose magnets on their periphery, forcing them to spend more time in places with more neighbors. The experimental platform was complemented by precise computer simulations conducted by Georgia Tech physics student Shengkai Li to investigate aspects of the system that are inconvenient to study in the laboratory.

Despite the simplicity of BOBbots, researchers found that when robots move and collide with each other, “compact aggregates form which are able to collectively release debris too heavy for one to move.” , according to Goldman. “While most people are building increasingly complex and expensive robots to ensure coordination, we wanted to see what complex tasks could be accomplished with very simple robots.”

Their work, as reported on April 23, 2021 in the newspaper Scientific progress, was inspired by a theoretical model of particles moving on a chessboard. A theoretical abstraction known as the self-organizing particle system was developed to rigorously study a mathematical model of BOBbots. Using ideas from probability theory, statistical physics, and stochastic algorithms, the researchers were able to prove that the theoretical model undergoes a phase change as the magnetic interactions increase – changing sharply from scattered to aggregated. in large, compact groups, similar to the phase changes we see in common daily systems, such as water and ice.

“The rigorous analysis not only showed us how to build the BOBbots, but also revealed an inherent robustness in our algorithm that allowed some of the robots to be faulty or unpredictable,” notes Randall, who is also a professor of computer science and auxiliary. math professor at Georgia Tech.

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