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- Summary:
- Inspired by a theoretical model of particles moving around on a chessboard, new robot swarm research shows that, as magnetic interactions increase, dispersed 'dumb robots' can abruptly gather in large, compact clusters to accomplish complex tasks. Researchers report that these 'BOBbots' (behaving, organizing, buzzing bots) are also capable of collectively clearing debris that is too heavy for one alone to move, thanks to a robust algorithm.
Anyone with children knows that while controlling one child can be hard, controlling many at once can be nearly impossible by Georgia Institute of Technology.
Getting swarms of robots to work collectively can be
equally challenging, unless researchers carefully choreograph their
interactions -- like planes in formation -- using increasingly
sophisticated components and algorithms. But what can be reliably
accomplished when the robots on hand are simple, inconsistent, and lack
sophisticated programming for coordinated behavior?
Photo: Science and Technology
A team of researchers led by Dana Randall, ADVANCE Professor of Computing and Daniel Goldman, Dunn Family Professor of Physics, both at Georgia Institute of Technology, sought to show that even the simplest of robots can still accomplish tasks well beyond the capabilities of one, or even a few, of them. The goal of accomplishing these tasks with what the team dubbed "dumb robots" (essentially mobile granular particles) exceeded their expectations, and the researchers report being able to remove all sensors, communication, memory and computation -- and instead accomplishing a set of tasks through leveraging the robots' physical characteristics, a trait that the team terms "task embodiment."...
Their work, as reported April 23, 2021 in the journal Science Advances, was inspired by a theoretical model of particles moving around on a chessboard. A theoretical abstraction known as a self-organizing particle system was developed to rigorously study a mathematical model of the 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 -- abruptly changing from dispersed to aggregating in large, compact clusters, similar to phase changes we see in common everyday systems, like water and ice.
Additional resources
Journal Reference:
- Shengkai Li, Bahnisikha Dutta, Sarah Cannon, Joshua J. Daymude, Ram Avinery, Enes Aydin, Andréa W. Richa, Daniel I. Goldman, Dana Randall. Programming active cohesive granular matter with mechanically induced phase changes. Science Advances, 2021; 7 (17): eabe8494 DOI: 10.1126/sciadv.abe8494
Source: Science Daily
