SCIENTISTS have developed “single cell” robots that can work together to perform complex tasks.
They are able to pick up nearby objects, navigate around obstacles and squeeze through tight gaps.
Felice Frankel Scientists have developed ‘single cell’ robots that can work together to perform complex tasks
The particle robots connect magnetically to move and work in a swarm without communicating or relying on one another, the US team found.
Prof Hod Lipson, of Columbia Engineering, said: “You have a new kind of robot that has no centralised control, no single point of failure, no fixed shape, and its components have no unique identity.”
Researchers say the development presents a new way to think about robots, which are traditionally designed for one purpose, comprise many complex parts, and stop working when any part malfunctions.
Known as “particle robots” they use an algorithm to take in levels of lights in their surroundings – they then connect to each other magnetically to move and work in a swarm.
Shuguang Li/Columbia Engineering Researchers say the development presents a new way to think about robots
These new robots could enable more flexible and robust systems because although they work together, they do not depend on each other to work.
Based on a project by MIT, Columbia Engineering, Cornell University, and Harvard University researchers, the so-called “particle robotics” system is made up of many simple individual disc-shaped devices, which the researchers call “particles”.
The particles are loosely connected by magnets around their perimeters, and each unit can only do two things – expand and contract.
When carefully timed that motion allows the individual particles to push and pull one another in coordinated movement while on-board sensors enable the cluster to gravitate toward light sources.
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None of the particles directly communicate with or rely on one another to function, so individual robots can be added or taken away without any impact on the group.
This means the particle robotic systems can complete tasks even when many units malfunction.
The paper was published in Nature on March 20.
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